PASS Documentation

Use the links below to load individual chapters from the PASS statistical software training documentation in PDF format. The chapters correspond to the procedures available in PASS. Each chapter generally has an introduction to the topic, technical details (including power and sample size calculation details), explanations for the procedure options, examples, and procedure validation examples. Each of these chapters is also available through the PASS Help System when running the software.

Jump to topic:

• Quick Start
• Introduction
• Assurance
• Bayesian Approaches
• Bridging Studies
• Cluster-Randomized
• Conditional Power
• Confidence Intervals
• Correlation
• Design of Experiments
• Equivalence
• GEE
• Group-Sequential
• Means
• Meta-Analysis
• Method Comparison
• Microarray
• Mixed Models
• Non-Inferiority
• Nonparametric
• Normality
• Pilot Studies
• Post-Marketing Surveillance
• Proportions
• Quality Control
• Rates and Counts
• Regression
• ROC
• Sample Size Reestimation
• Simulation
• Stratified
• Superiority by a Margin
• Survival
• Tolerance Intervals
• Vaccine Efficacy
• Variances
• Tools
• Plots
• References

Quick Start

• Quick Start

Introduction

• License Agreement
• The PASS Home Window
• The Procedure Window
• The Output Window
• Introduction to Power Analysis
• Power Analysis of Proportions
• Power Analysis of Means

Assurance

Means

Inequality

• Assurance for Two-Sample T-Tests Assuming Equal Variance
• Assurance for Two-Sample T-Tests Allowing Unequal Variance
• Assurance for Two-Sample Z-Tests Assuming Equal Variance
• Assurance for Tests for Two Means in a Cluster-Randomized Design

Non-Inferiority

• Assurance for Two-Sample T-Tests for Non-Inferiority Assuming Equal Variance
• Assurance for Two-Sample T-Tests for Non-Inferiority Allowing Unequal Variance
• Assurance for Non-Inferiority Tests for Two Means in a Cluster-Randomized Design

Superiority by a Margin

• Assurance for Two-Sample T-Tests for Superiority by a Margin Assuming Equal Variance
• Assurance for Two-Sample T-Tests for Superiority by a Margin Allowing Unequal Variance
• Assurance for Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design

Equivalence

• Assurance for Two-Sample T-Tests for Equivalence Assuming Equal Variance
• Assurance for Two-Sample T-Tests for Equivalence Allowing Unequal Variance
• Assurance for Equivalence Tests for Two Means in a Cluster-Randomized Design

Cluster-Randomized

• Assurance for Tests for Two Means in a Cluster-Randomized Design
• Assurance for Non-Inferiority Tests for Two Means in a Cluster-Randomized Design
• Assurance for Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design
• Assurance for Equivalence Tests for Two Means in a Cluster-Randomized Design

Proportions

Inequality

• Assurance for Tests for Two Proportions
• Assurance for Tests for Two Proportions in a Cluster-Randomized Design

Non-Zero Null

• Assurance for Non-Zero Null Tests for the Difference Between Two Proportions
• Assurance for Non-Unity Null Tests for the Ratio of Two Proportions
• Assurance for Non-Unity Null Tests for the Odds Ratio of Two Proportions
• Assurance for Non-Zero Null Tests for the Difference of Two Proportions in a Cluster-Randomized Design

Non-Inferiority

• Assurance for Non-Inferiority Tests for the Difference Between Two Proportions
• Assurance for Non-Inferiority Tests for the Ratio of Two Proportions
• Assurance for Non-Inferiority Tests for the Odds Ratio of Two Proportions
• Assurance for Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Assurance for Non-Inferiority Tests for the Difference of Two Proportions in a Cluster-Randomized Design

Superiority by a Margin

• Assurance for Superiority by a Margin Tests for the Difference Between Two Proportions
• Assurance for Superiority by a Margin Tests for the Ratio of Two Proportions
• Assurance for Superiority by a Margin Tests for the Odds Ratio of Two Proportions
• Assurance for Superiority by a Margin Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions

Equivalence

• Assurance for Equivalence Tests for the Difference Between Two Proportions
• Assurance for Equivalence Tests for the Ratio of Two Proportions
• Assurance for Equivalence Tests for the Odds Ratio of Two Proportions
• Assurance for Equivalence Tests for the Difference of Two Proportions in a Cluster-Randomized Design

Cluster-Randomized

• Assurance for Tests for Two Proportions in a Cluster-Randomized Design
• Assurance for Non-Zero Null Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Non-Inferiority Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Superiority by a Margin Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Equivalence Tests for the Difference of Two Proportions in a Cluster-Randomized Design

Vaccine Efficacy

• Assurance for Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Assurance for Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions

Rates and Counts

Inequality

• Assurance for Tests for the Difference Between Two Poisson Rates
• Assurance for Tests for the Ratio of Two Poisson Rates
• Assurance for Tests for the Ratio of Two Negative Binomial Rates

Non-Inferiority

• Assurance for Non-Inferiority Tests for the Ratio of Two Poisson Rates
• Assurance for Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates

Superiority by a Margin

• Assurance for Superiority by a Margin Tests for the Ratio of Two Poisson Rates
• Assurance for Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates

Equivalence

• Assurance for Equivalence Tests for the Ratio of Two Poisson Rates
• Assurance for Equivalence Tests for the Ratio of Two Negative Binomial Rates

Poisson Rates

• Assurance for Tests for the Difference Between Two Poisson Rates
• Assurance for Tests for the Ratio of Two Poisson Rates
• Assurance for Non-Inferiority Tests for the Ratio of Two Poisson Rates
• Assurance for Superiority by a Margin Tests for the Ratio of Two Poisson Rates
• Assurance for Equivalence Tests for the Ratio of Two Poisson Rates

Negative Binomial Rates

• Assurance for Tests for the Ratio of Two Negative Binomial Rates
• Assurance for Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
• Assurance for Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
• Assurance for Equivalence Tests for the Ratio of Two Negative Binomial Rates

Survival

Inequality

• Assurance for Logrank Tests (Freedman)
• Assurance for Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Assurance for Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Assurance for Logrank Tests in a Cluster-Randomized Design

Non-Inferiority

• Assurance for Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Assurance for Non-Inferiority Tests for the Difference of Two Hazard Rates Assuming an Exponential Model

Superiority by a Margin

• Assurance for Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Assurance for Superiority by a Margin Tests for the Difference of Two Hazard Rates Assuming an Exponential Model

Equivalence

• Assurance for Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Assurance for Equivalence Tests for the Difference of Two Hazard Rates Assuming an Exponential Model

Cluster-Randomized

• Assurance for Logrank Tests in a Cluster-Randomized Design

Vaccine Efficacy

Proportions

• Assurance for Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Assurance for Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions

Bayesian Approaches

• Bayesian Adjustment using the Posterior Error Approach
• Tests for Two Means Assuming Equal Variances using a Bayesian Approach
• Dose-Finding using the Bayesian Continual Reassessment Method (CRM)

Bridging Studies

Means

• Bridging Study using a Non-Inferiority Test of Two Groups (Continuous Outcome)
• Bridging Study using the Equivalence Test of Two Groups (Continuous Outcome)
• Bridging Study Test of Sensitivity using a Two-Group T-Test (Continuous Outcome)

Proportions

• Bridging Study using a Non-Inferiority Test of Two Groups (Binary Outcome)
• Bridging Study using the Equivalence Test of Two Groups (Binary Outcome)

Sensitivity

• Bridging Study Sensitivity Index
• Bridging Study Test of Sensitivity using a Two-Group T-Test (Continuous Outcome)

Cluster-Randomized

One Mean

Confidence Interval

• Confidence Intervals for One Mean in a Cluster-Randomized Design
• Confidence Intervals for One Mean in a Stratified Cluster-Randomized Design

Two Means

Test (Inequality)

• Tests for Two Means in a Cluster-Randomized Design
• Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm
• Tests for Two Means in a Stepped-Wedge Cluster-Randomized Design
• Tests for the Matched-Pair Difference of Two Means in a Cluster-Randomized Design
• GEE Tests for Two Means in a Cluster-Randomized Design
• GEE Tests for Two Means in a Stratified Cluster-Randomized Design
• GEE Tests for Two Means in a Split-Mouth Design

Non-Inferiority

• Non-Inferiority Tests for Two Means in a Cluster-Randomized Design
• Non-Inferiority Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm

Superiority by a Margin

• Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design

Equivalence

• Equivalence Tests for Two Means in a Cluster-Randomized Design

Mixed Models (2-Level Hierarchical Design)

• Mixed Models Tests for Two Means in a Cluster-Randomized Design
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Means at the End of Follow-Up in a 2-Level Hierarchical Design

Mixed Models (3-Level Hierarchical Design)

• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Means at the End of Follow-Up in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Fixed Slopes (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-2 Randomization)

GEE

• GEE Tests for Two Means in a Cluster-Randomized Design
• GEE Tests for Two Means in a Stratified Cluster-Randomized Design
• GEE Tests for Two Means in a Split-Mouth Design

Meta-Analysis

• Meta-Analysis of Tests for Two Means using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for Two Means using a Random-Effects Model in a Cluster-Randomized Design

Multiple Means

Mixed Models (Interaction in a 2×2 Factorial Design)

• Mixed Models Tests for Interaction in a 2×2 Factorial 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-2 Randomization)

Mixed Models (Slope-Interaction in a 2×2 Factorial Design)

• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 2-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 2-Level Hierarchical Design with Random Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Fixed Slopes (Level-3 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Random Slopes (Level-2 Randomization)

GEE Tests for Multiple Groups

• GEE Tests for Multiple Means in a Cluster-Randomized Design
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Continuous Outcome)

Multi-Arm Tests vs. a Control

• Multi-Arm Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for Treatment and Control Means in a Cluster-Randomized Design

One Proportion

Confidence Interval

• Confidence Intervals for One Proportion in a Cluster-Randomized Design
• Confidence Intervals for One Proportion in a Stratified Cluster-Randomized Design

Two Proportions

Test (Inequality)

• Tests for Two Proportions in a Cluster-Randomized Design
• Tests for Two Proportions in a Cluster-Randomized Design with Clustering in Only One Arm
• Tests for Two Proportions in a Stratified Cluster-Randomized Design (Cochran-Mantel-Haenszel Test)
• Tests for Two Proportions in a Stepped-Wedge Cluster-Randomized Design
• Tests for the Matched-Pair Difference of Two Proportions in a Cluster-Randomized Design
• GEE Tests for Two Proportions in a Split-Mouth Design

Test (Non-Zero Null)

• Non-Zero Null Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Non-Unity Null Tests for the Ratio of Two Proportions in a Cluster-Randomized Design

Non-Inferiority

• Non-Inferiority Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design with Clustering in Only One Arm
• Non-Inferiority Tests for the Ratio of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design

Superiority by a Margin

• Superiority by a Margin Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design

Equivalence

• Equivalence Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Equivalence Tests for the Ratio of Two Proportions in a Cluster-Randomized Design

Mixed Models (2-Level Hierarchical Design)

• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-1 Randomization)

Mixed Models (3-Level Hierarchical Design)

• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-1 Randomization)

GEE

• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for Two Proportions in a Split-Mouth Design

Vaccine Efficacy

• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design

Meta-Analysis

• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Random-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Random-Effects Model in a Cluster-Randomized Design

Multiple Proportions

• GEE Tests for Multiple Proportions in a Cluster-Randomized Design
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Binary Outcome)
• Multi-Arm Tests for Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for the Difference of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for the Difference of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for the Difference of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design

Rates and Counts

• Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design with Adjustment for Varying Cluster Sizes
• Non-Inferiority Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Tests for Two Poisson Rates in a Stepped-Wedge Cluster-Randomized Design
• Tests for the Matched-Pair Difference of Two Event Rates in a Cluster-Randomized Design
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design

Survival

• Logrank Tests in a Cluster-Randomized Design
• Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design

Stepped-Wedge

• Tests for Two Means in a Stepped-Wedge Cluster-Randomized Design
• Tests for Two Proportions in a Stepped-Wedge Cluster-Randomized Design
• Tests for Two Poisson Rates in a Stepped-Wedge Cluster-Randomized Design

Mixed Models

Means

• Mixed Models Tests for Two Means in a Cluster-Randomized Design
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Means at the End of Follow-Up in a 2-Level Hierarchical Design
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Means at the End of Follow-Up in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 2-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 2-Level Hierarchical Design with Random Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Fixed Slopes (Level-3 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Random Slopes (Level-2 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Fixed Slopes (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-2 Randomization)

Proportions

• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-1 Randomization)

GEE

Means

• GEE Tests for Two Means in a Cluster-Randomized Design
• GEE Tests for Two Means in a Stratified Cluster-Randomized Design
• GEE Tests for Two Means in a Split-Mouth Design
• GEE Tests for Multiple Means in a Cluster-Randomized Design
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Continuous Outcome)

Proportions

• GEE Tests for Multiple Proportions in a Cluster-Randomized Design
• GEE Tests for Two Proportions in a Split-Mouth Design
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Binary Outcome)

Rates and Counts

• GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Count Outcome)

Vaccine Efficacy

• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design

Assurance

• Assurance for Tests for Two Means in a Cluster-Randomized Design
• Assurance for Non-Inferiority Tests for Two Means in a Cluster-Randomized Design
• Assurance for Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design
• Assurance for Equivalence Tests for Two Means in a Cluster-Randomized Design
• Assurance for Tests for Two Proportions in a Cluster-Randomized Design
• Assurance for Non-Zero Null Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Non-Inferiority Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Superiority by a Margin Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Equivalence Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Logrank Tests in a Cluster-Randomized Design

Meta-Analysis

• Meta-Analysis of Tests for Two Means using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for Two Means using a Random-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Random-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Random-Effects Model in a Cluster-Randomized Design

Conditional Power

Means

Test (Inequality)

• Conditional Power and Sample Size Reestimation of One-Sample T-Tests
• Conditional Power and Sample Size Reestimation of Paired T-Tests
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests
• Conditional Power and Sample Size Reestimation of Tests for Two Means in a 2x2 Cross-Over Design

Non-Inferiority

• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design

Superiority by a Margin

• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design

Proportions

Test (Inequality)

• Conditional Power and Sample Size Reestimation of Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Tests for the Difference Between Two Proportions

Non-Inferiority

• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Proportions

Superiority by a Margin

• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Proportions

Survival

Test (Inequality)

• Conditional Power and Sample Size Reestimation of Logrank Tests

Non-Inferiority

• Conditional Power and Sample Size Reestimation of Non-Inferiority Logrank Tests

Superiority by a Margin

• Conditional Power and Sample Size Reestimation of Superiority by a Margin Logrank Tests

Confidence Intervals

Correlation

• Confidence Intervals for Pearson's Correlation
• Confidence Intervals for Spearman's Rank Correlation
• Confidence Intervals for Kendall's Tau-b Correlation
• Confidence Intervals for Point Biserial Correlation
• Confidence Intervals for Intraclass Correlation
• Confidence Intervals for Intraclass Correlation with Assurance Probability (Two-Sided)
• Confidence Intervals for Intraclass Correlation with Assurance Probability (Lower One-Sided)
• Confidence Intervals for Coefficient Alpha
• Confidence Intervals for Kappa

Means

• Confidence Intervals for One Mean
• Confidence Intervals for One Mean with Tolerance Probability
• Confidence Intervals for One Mean in a Stratified Design
• Confidence Intervals for One Mean in a Cluster-Randomized Design
• Confidence Intervals for One Mean in a Stratified Cluster-Randomized Design
• Confidence Intervals for Paired Means
• Confidence Intervals for Paired Means with Tolerance Probability
• Confidence Intervals for the Difference Between Two Means
• Confidence Intervals for the Difference Between Two Means with Tolerance Probability
• Confidence Intervals for One-Way Repeated Measures Contrasts

Method Comparison

• Confidence Intervals for the Bland-Altman Range of Agreement using Assurance Probability
• Confidence Intervals for the Bland-Altman Range of Agreement using Expected Half-Width

Percentiles

• Confidence Intervals for a Percentile of a Normal Distribution
• Confidence Intervals for a Percentile of a Normal Distribution using Assurance Probability
• Confidence Intervals for a Percentile of a Normal Distribution using Expected Width
• Confidence Intervals for Regression-Based Reference Limits using Assurance Probability
• Confidence Intervals for Regression-Based Reference Limits using Expected Relative Precision
• Confidence Intervals for an Exponential Lifetime Percentile

Proportions

• Confidence Intervals for One Proportion
• Confidence Intervals for One Proportion from a Finite Population
• Confidence Intervals for One Proportion in a Stratified Design
• Confidence Intervals for One Proportion in a Cluster-Randomized Design
• Confidence Intervals for One Proportion in a Stratified Cluster-Randomized Design
• Confidence Intervals for the Difference Between Two Proportions
• Confidence Intervals for the Ratio of Two Proportions
• Confidence Intervals for the Difference Between Two Correlated Proportions
• Confidence Intervals for Vaccine Efficacy using a Cohort Design
• Confidence Intervals for Vaccine Efficacy using an Unmatched Case-Control Design
• Confidence Intervals for the Odds Ratio of Two Proportions using an Unmatched Case-Control Design
• Confidence Intervals for the Odds Ratio of Two Proportions
• Confidence Intervals for Kappa

Quality Control

• Confidence Intervals for Cp
• Confidence Intervals for Cpk

Reference Intervals

• Reference Intervals for Normal Data
• Nonparametric Reference Intervals for Non-Normal Data
• Reference Intervals for Clinical and Lab Medicine
• Confidence Intervals for Regression-Based Reference Limits using Assurance Probability
• Confidence Intervals for Regression-Based Reference Limits using Expected Relative Precision

Regression

• Confidence Intervals for Linear Regression Slope
• Confidence Intervals for the Odds Ratio in Logistic Regression with One Binary X
• Confidence Intervals for the Odds Ratio in Logistic Regression with Two Binary X's
• Confidence Intervals for the Interaction Odds Ratio in Logistic Regression with Two Binary X's
• Confidence Intervals for Michaelis-Menten Parameters
• Reference Intervals for Clinical and Lab Medicine
• Confidence Intervals for Regression-Based Reference Limits using Assurance Probability
• Confidence Intervals for Regression-Based Reference Limits using Expected Relative Precision

ROC

• Confidence Intervals for the Area Under an ROC Curve

Sensitivity and Specificity

• Confidence Intervals for One-Sample Sensitivity
• Confidence Intervals for One-Sample Specificity
• Confidence Intervals for One-Sample Sensitivity and Specificity

Standard Deviation

• Confidence Intervals for One Standard Deviation using Standard Deviation
• Confidence Intervals for One Standard Deviation using Relative Error
• Confidence Intervals for One Standard Deviation with Tolerance Probability

Survival

• Confidence Intervals for the Exponential Lifetime Mean
• Confidence Intervals for an Exponential Lifetime Percentile
• Confidence Intervals for Exponential Reliability
• Confidence Intervals for the Exponential Hazard Rate
• Confidence Intervals for the Weibull Shape Parameter

Variances

• Confidence Intervals for One Variance using Variance
• Confidence Intervals for One Variance using Relative Error
• Confidence Intervals for One Variance with Tolerance Probability
• Confidence Intervals for the Ratio of Two Variances using Variances
• Confidence Intervals for the Ratio of Two Variances using Relative Error

Correlation

Correlation

Test (Inequality)

• Pearson's Correlation Tests
• Pearson's Correlation Tests (Simulation)
• Spearman's Rank Correlation Tests (Simulation)
• Kendall's Tau-b Correlation Tests (Simulation)
• Power Comparison of Correlation Tests (Simulation)
• Tests for Two Correlations
• Point Biserial Correlation Tests

Confidence Interval

• Confidence Intervals for Pearson's Correlation
• Confidence Intervals for Spearman's Rank Correlation
• Confidence Intervals for Kendall's Tau-b Correlation
• Confidence Intervals for Point Biserial Correlation

Coefficient (Cronbach's) Alpha

• Tests for One Coefficient Alpha
• Tests for Two Coefficient Alphas
• Confidence Intervals for Coefficient Alpha

Intraclass Correlation

• Tests for Intraclass Correlation
• Confidence Intervals for Intraclass Correlation
• Confidence Intervals for Intraclass Correlation with Assurance Probability (Two-Sided)
• Confidence Intervals for Intraclass Correlation with Assurance Probability (Lower One-Sided)

Kappa Rater Agreement

• Kappa Test for Agreement Between Two Raters
• Confidence Intervals for Kappa

Meta-Analysis

• Meta-Analysis of Correlation Tests using a Fixed-Effects Model
• Meta-Analysis of Correlation Tests using a Random-Effects Model

Lin's Concordance Correlation

• Lin's Concordance Correlation Coefficient

Design of Experiments

Randomization Lists

• Randomization Lists

Experimental Design

• Balanced Incomplete Block Designs
• D-Optimal Designs
• Design Generator
• Fractional Factorial Designs
• Latin Square Designs
• Response Surface Designs
• Screening Designs
• Taguchi Designs
• Two-Level Designs

Equivalence

Means

One Mean

• One-Sample Z-Tests for Equivalence
• One-Sample T-Tests for Equivalence

Paired Means

• Paired Z-Tests for Equivalence
• Paired T-Tests for Equivalence
• Equivalence Tests for Paired Means (Simulation)

Two Independent Means

• Two-Sample T-Tests for Equivalence Assuming Equal Variance
• Two-Sample T-Tests for Equivalence Allowing Unequal Variance
• Equivalence Tests for Two Means (Simulation)
• Equivalence Tests for the Ratio of Two Means (Log-Normal Data)
• Equivalence Tests for the Ratio of Two Means (Normal Data)
• Bridging Study using the Equivalence Test of Two Groups (Continuous Outcome)
• Biosimilarity Tests for the Difference Between Means using a Parallel Two-Group Design

Two Means (Cluster-Randomized)

• Equivalence Tests for Two Means in a Cluster-Randomized Design

Multiple Means

• Equivalence Tests for One-Way Analysis of Variance Assuming Equal Variances
• Equivalence Tests for One-Way Analysis of Variance Allowing Unequal Variances
• Studentized Range Tests for Equivalence
• Equivalence Tests for the Mean Ratio in a Three-Arm Trial (Normal Data) (Simulation)
• Multi-Arm Equivalence Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
• Multi-Arm Equivalence Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
• Multi-Arm Equivalence Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Means (Normal Data)
• Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Means (Log-Normal Data)

Cross-Over (2x2) Design

• Equivalence Tests for the Difference Between Two Means in a 2x2 Cross-Over Design
• Equivalence Tests for the Ratio of Two Means in a 2x2 Cross-Over Design (Log-Normal Data)
• Equivalence Tests for the Ratio of Two Means in a 2x2 Cross-Over Design (Normal Data)
• Bioequivalence Tests for AUC and Cmax in a 2x2 Cross-Over Design (Log-Normal Data)
• Equivalence Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design

Cross-Over (Higher-Order) Design

• Equivalence Tests for the Difference of Two Means in a Higher-Order Cross-Over Design
• Equivalence Tests for the Ratio of Two Means in a Higher-Order Cross-Over Design (Log-Normal Data)

Cross-Over (Williams) Design

• Equivalence Tests for Pairwise Mean Differences in a Williams Cross-Over Design

Biosimilar

• Biosimilarity Tests for the Difference Between Means using a Parallel Two-Group Design

Proportions

One Proportion

• Equivalence Tests for One Proportion

Two Correlated (Paired) Proportions

• Equivalence Tests for the Difference Between Two Correlated Proportions
• Equivalence Tests for the Ratio of Two Correlated Proportions

Two Independent Proportions

• Equivalence Tests for the Difference Between Two Proportions
• Equivalence Tests for the Ratio of Two Proportions
• Equivalence Tests for the Odds Ratio of Two Proportions
• Bridging Study using the Equivalence Test of Two Groups (Binary Outcome)

Two Proportions (Cluster-Randomized)

• Equivalence Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Equivalence Tests for the Ratio of Two Proportions in a Cluster-Randomized Design

Multiple Proportions (Multi-Arm Tests vs. a Control)

• Multi-Arm Equivalence Tests for the Difference Between Treatment and Control Proportions
• Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Proportions
• Multi-Arm Equivalence Tests for the Odds Ratio of Treatment and Control Proportions
• Multi-Arm Equivalence Tests for the Difference of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design

Cross-Over (2×2) Design

• Equivalence Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
• Equivalence Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
• Equivalence Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design

Cross-Over (Williams) Design

• Equivalence Tests for Pairwise Proportion Differences in a Williams Cross-Over Design

Rates and Counts

• Equivalence Tests for the Ratio of Two Poisson Rates
• Equivalence Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
• Equivalence Tests for the Ratio of Two Negative Binomial Rates

Survival

• Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
• Multi-Arm Equivalence Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Equivalence Tests for the Difference of Two Hazard Rates Assuming an Exponential Model

Variances

• Equivalence Tests for the Ratio of Two Variances
• Equivalence Tests for the Ratio of Two Within-Subject Variances in a Parallel Design
• Equivalence Tests for the Ratio of Two Within-Subject Variances in a 2×2M Replicated Cross-Over Design
• Equivalence Tests for the Difference of Two Within-Subject CV's in a Parallel Design

Assurance

• Assurance for Two-Sample T-Tests for Equivalence Assuming Equal Variance
• Assurance for Two-Sample T-Tests for Equivalence Allowing Unequal Variance
• Assurance for Equivalence Tests for Two Means in a Cluster-Randomized Design
• Assurance for Equivalence Tests for the Difference Between Two Proportions
• Assurance for Equivalence Tests for the Ratio of Two Proportions
• Assurance for Equivalence Tests for the Odds Ratio of Two Proportions
• Assurance for Equivalence Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Equivalence Tests for the Ratio of Two Poisson Rates
• Assurance for Equivalence Tests for the Ratio of Two Negative Binomial Rates
• Assurance for Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Assurance for Equivalence Tests for the Difference of Two Hazard Rates Assuming an Exponential Model

GEE

Means

• GEE Tests for Two Means in a Cluster-Randomized Design
• GEE Tests for Two Means in a Stratified Cluster-Randomized Design
• GEE Tests for Two Means in a Split-Mouth Design
• GEE Tests for Multiple Means in a Cluster-Randomized Design
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Continuous Outcome)

Proportions

• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for Two Correlated Proportions with Dropout
• GEE Tests for Two Proportions in a Split-Mouth Design
• GEE Tests for Multiple Proportions in a Cluster-Randomized Design

Rates and Counts

• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design

Group-Sequential

One Mean

Test (Inequality)

• Group-Sequential Tests for One Mean with Known Variance (Simulation)
• Group-Sequential T-Tests for One Mean (Simulation)

Non-Inferiority

• Group-Sequential Non-Inferiority Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Non-Inferiority T-Tests for One Mean (Simulation)

Superiority by a Margin

• Group-Sequential Superiority by a Margin Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for One Mean (Simulation)

Two Means

Test (Inequality)

• Group-Sequential Tests for Two Means with Known Variances (Simulation)
• Group-Sequential T-Tests for Two Means (Simulation)
• Group-Sequential Tests for Two Means (Legacy)
• Group-Sequential Tests for Two Means (Simulation) (Legacy)
• Group-Sequential Tests for Two Means Assuming Normality (Simulation) (Legacy)

Non-Inferiority

• Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Means (Simulation) (Legacy)

Superiority by a Margin

• Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation)

One Proportion

Test (Inequality)

• Group-Sequential Tests for One Proportion (Simulation)
• Group-Sequential Tests for One Proportion in a Fleming Design
• Single-Stage Phase II Clinical Trials
• Two-Stage Designs for Tests of One Proportion (Simon)
• Three-Stage Phase II Clinical Trials

Non-Inferiority

• Group-Sequential Non-Inferiority Tests for One Proportion (Simulation)

Superiority by a Margin

• Group-Sequential Superiority by a Margin Tests for One Proportion (Simulation)

Two Proportions

Test (Inequality)

• Group-Sequential Tests for Two Proportions (Simulation)
• Group-Sequential Tests for Two Proportions (Legacy)
• Group-Sequential Tests for Two Proportions (Simulation) (Legacy)

Non-Inferiority

• Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for the Ratio of Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for the Odds Ratio of Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for the Difference of Two Proportions (Simulation) (Legacy)

Superiority by a Margin

• Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for the Ratio of Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for the Odds Ratio of Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for the Difference of Two Proportions (Simulation) (Legacy)

Survival

Test (Inequality)

• Group-Sequential Tests for One Hazard Rate (Simulation)
• Group-Sequential Tests for Two Hazard Rates (Simulation)
• Group-Sequential Logrank Tests (Legacy)
• Group-Sequential Logrank Tests (Simulation) (Legacy)

Non-Inferiority

• Group-Sequential Non-Inferiority Tests for One Hazard Rate (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Hazard Rates (Simulation)

Superiority by a Margin

• Group-Sequential Superiority by a Margin Tests for One Hazard Rate (Simulation)
• Group-Sequential Superiority by a Margin Tests for Two Hazard Rates (Simulation)

Poisson Rates

Test (Inequality)

• Group-Sequential Tests for One Poisson Rate (Simulation)
• Group-Sequential Tests for Two Poisson Rates (Simulation)

Non-Inferiority

• Group-Sequential Non-Inferiority Tests for One Poisson Rate (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Poisson Rates (Simulation)

Superiority by a Margin

• Group-Sequential Superiority by a Margin Tests for One Poisson Rate (Simulation)
• Group-Sequential Superiority by a Margin Tests for Two Poisson Rates (Simulation)

Means

One Mean

T-Test (Inequality)

• One-Sample T-Tests
• One-Sample T-Tests using Effect Size
• Tests for One Mean (Simulation)
• Wilcoxon Signed-Rank Tests
• Conditional Power and Sample Size Reestimation of One-Sample T-Tests
• Group-Sequential T-Tests for One Mean (Simulation)
• Multiple Testing for One Mean (One-Sample or Paired Data)

Z-Test (Inequality)

• One-Sample Z-Tests
• Group-Sequential Tests for One Mean with Known Variance (Simulation)
• Multiple Testing for One Mean (One-Sample or Paired Data)

Nonparametric

• Tests for One Mean (Simulation)
• Wilcoxon Signed-Rank Tests
• Wilcoxon Signed-Rank Tests for Non-Inferiority
• Wilcoxon Signed-Rank Tests for Superiority by a Margin
• Multiple Testing for One Mean (One-Sample or Paired Data)
• Confidence Intervals for a Percentile of a Normal Distribution
• Confidence Intervals for a Percentile of a Normal Distribution using Assurance Probability
• Confidence Intervals for a Percentile of a Normal Distribution using Expected Width

Non-Normal Data

• Tests for One Mean (Simulation)
• Tests for One Exponential Mean
• Tests for One Poisson Rate
• Wilcoxon Signed-Rank Tests
• Wilcoxon Signed-Rank Tests for Non-Inferiority
• Wilcoxon Signed-Rank Tests for Superiority by a Margin
• Multiple Testing for One Mean (One-Sample or Paired Data)

Confidence Interval

• Confidence Intervals for One Mean
• Confidence Intervals for One Mean with Tolerance Probability
• Confidence Intervals for One Mean in a Stratified Design
• Confidence Intervals for One Mean in a Cluster-Randomized Design
• Confidence Intervals for One Mean in a Stratified Cluster-Randomized Design
• Confidence Intervals for a Percentile of a Normal Distribution
• Confidence Intervals for a Percentile of a Normal Distribution using Assurance Probability
• Confidence Intervals for a Percentile of a Normal Distribution using Expected Width
• Confidence Intervals for Regression-Based Reference Limits using Assurance Probability
• Confidence Intervals for Regression-Based Reference Limits using Expected Relative Precision

Non-Inferiority

• One-Sample Z-Tests for Non-Inferiority
• One-Sample T-Tests for Non-Inferiority
• Wilcoxon Signed-Rank Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Non-Inferiority
• Group-Sequential Non-Inferiority Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Non-Inferiority T-Tests for One Mean (Simulation)

Superiority by a Margin

• One-Sample Z-Tests for Superiority by a Margin
• One-Sample T-Tests for Superiority by a Margin
• Wilcoxon Signed-Rank Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Superiority by a Margin
• Group-Sequential Superiority by a Margin Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for One Mean (Simulation)

Equivalence

• One-Sample Z-Tests for Equivalence
• One-Sample T-Tests for Equivalence

Stratified

• Confidence Intervals for One Mean in a Stratified Design
• Confidence Intervals for One Mean in a Stratified Cluster-Randomized Design

Multiple Testing

• Multiple Testing for One Mean (One-Sample or Paired Data)

Group-Sequential

• Group-Sequential Tests for One Mean with Known Variance (Simulation)
• Group-Sequential T-Tests for One Mean (Simulation)
• Group-Sequential Non-Inferiority Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Non-Inferiority T-Tests for One Mean (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for One Mean (Simulation)

Conditional Power

• Conditional Power and Sample Size Reestimation of One-Sample T-Tests
• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Superiority by a Margin

Paired Means

T-Test (Inequality)

• Paired T-Tests
• Paired T-Tests using Effect Size
• Tests for Paired Means (Simulation)
• Paired Wilcoxon Signed-Rank Tests
• Multiple Testing for One Mean (One-Sample or Paired Data)
• Tests for the Matched-Pair Difference of Two Means in a Cluster-Randomized Design
• Conditional Power and Sample Size Reestimation of Paired T-Tests
• Tests for Paired Means (Simulation) (Legacy)

Z-Test (Inequality)

• Paired Z-Tests
• Multiple Testing for One Mean (One-Sample or Paired Data)

Nonparametric

• Tests for Paired Means (Simulation)
• Paired Wilcoxon Signed-Rank Tests
• Paired Wilcoxon Signed-Rank Tests for Non-Inferiority
• Paired Wilcoxon Signed-Rank Tests for Superiority by a Margin
• Equivalence Tests for Paired Means (Simulation)
• Multiple Testing for One Mean (One-Sample or Paired Data)
• Tests for Paired Means (Simulation) (Legacy)

Confidence Interval

• Confidence Intervals for Paired Means
• Confidence Intervals for Paired Means with Tolerance Probability

Non-Inferiority

• Paired Z-Tests for Non-Inferiority
• Paired T-Tests for Non-Inferiority
• Paired Wilcoxon Signed-Rank Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Non-Inferiority

Superiority by a Margin

• Paired Z-Tests for Superiority by a Margin
• Paired T-Tests for Superiority by a Margin
• Paired Wilcoxon Signed-Rank Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Superiority by a Margin

Equivalence

• Paired Z-Tests for Equivalence
• Paired T-Tests for Equivalence
• Equivalence Tests for Paired Means (Simulation)

Cluster-Randomized

• Tests for the Matched-Pair Difference of Two Means in a Cluster-Randomized Design

Single-Case (AB)ᴷ Designs

• Tests for the Difference Between Treatment and Control Means in a Balanced Single-Case (AB)ᴷ Design with Multiple Cases

Multiple Testing

• Multiple Testing for One Mean (One-Sample or Paired Data)

Conditional Power

• Conditional Power and Sample Size Reestimation of Paired T-Tests
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Superiority by a Margin

Meta-Analysis

• Meta-Analysis of Tests for Paired Means using a Fixed-Effects Model
• Meta-Analysis of Tests for Paired Means using a Random-Effects Model

Two Independent Means

T-Test (Inequality)

• Two-Sample T-Tests Assuming Equal Variance
• Two-Sample T-Tests Allowing Unequal Variance
• Two-Sample T-Tests using Effect Size
• Tests for Two Means (Simulation)
• Tests for Two Ordered Categorical Variables (Proportional Odds)
• Tests for Two Ordered Categorical Variables (Non-Proportional Odds)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Noether)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Guenther)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Simulation)
• Stratified Wilcoxon-Mann-Whitney (van Elteren) Test
• Tests for Two Means Assuming Equal Variances using a Bayesian Approach
• Tests for Two Groups Assuming a Two-Part Model
• Tests for Two Groups Assuming a Two-Part Model with Detection Limits
• Tests for the Ratio of Two Means (Log-Normal Data)
• Tests for the Ratio of Two Means (Normal Data)
• Tests for Fold Change of Two Means (Log-Normal Data)
• Tests for Two Means in a Cluster-Randomized Design
• Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm
• Multiple Testing for Two Means
• Mixed Models Tests for Two Means in a Cluster-Randomized Design
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-1 Randomization)
• GEE Tests for Two Means in a Cluster-Randomized Design
• GEE Tests for Two Means in a Stratified Cluster-Randomized Design
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests
• Bridging Study Test of Sensitivity using a Two-Group T-Test (Continuous Outcome)

Z-Test (Inequality)

• Two-Sample Z-Tests Assuming Equal Variance
• Two-Sample Z-Tests Allowing Unequal Variance
• Multiple Testing for Two Means

Nonparametric

• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Noether)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Guenther)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Simulation)
• Stratified Wilcoxon-Mann-Whitney (van Elteren) Test
• Tests for Two Means (Simulation)
• Tests for Two Ordered Categorical Variables (Proportional Odds)
• Tests for Two Ordered Categorical Variables (Non-Proportional Odds)
• Tests for Two Ordered Categorical Variables (Legacy)
• Stratified Wilcoxon-Mann-Whitney (van Elteren) Test
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Non-Inferiority
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Superiority by a Margin
• Equivalence Tests for Two Means (Simulation)
• Group-Sequential Tests for Two Means (Simulation) (Legacy)
• Group-Sequential Tests for Two Means Assuming Normality (Simulation) (Legacy)
• Group-Sequential Non-Inferiority Tests for Two Means (Simulation) (Legacy)
• Tests for Two Groups Assuming a Two-Part Model
• Tests for Two Groups Assuming a Two-Part Model with Detection Limits
• Multiple Testing for Two Means

Ratio Test

• Tests for the Ratio of Two Means (Log-Normal Data)
• Tests for the Ratio of Two Means (Normal Data)
• Non-Inferiority Tests for the Ratio of Two Means (Log-Normal Data)
• Non-Inferiority Tests for the Ratio of Two Means (Normal Data)
• Non-Inferiority Tests for the Ratio of Two Poisson Rates
• Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
• Superiority by a Margin Tests for the Ratio of Two Means (Log-Normal Data)
• Superiority by a Margin Tests for the Ratio of Two Means (Normal Data)
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
• Equivalence Tests for the Ratio of Two Means (Normal Data)
• Equivalence Tests for the Ratio of Two Means (Log-Normal Data)
• Equivalence Tests for the Ratio of Two Means in a 2x2 Cross-Over Design (Normal Data)
• Equivalence Tests for the Ratio of Two Poisson Rates
• Equivalence Tests for the Ratio of Two Negative Binomial Rates
• Tests for Fold Change of Two Means (Log-Normal Data)

Non-Normal Data

• Tests for Two Means (Simulation)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Noether)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Guenther)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Simulation)
• Stratified Wilcoxon-Mann-Whitney (van Elteren) Test
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Non-Inferiority
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Superiority by a Margin
• Multiple Testing for Two Means
• Tests for Two Exponential Means
• Tests for the Difference Between Two Poisson Rates
• Tests for the Ratio of Two Poisson Rates (Zhu)
• Tests for the Ratio of Two Poisson Rates (Gu)
• Non-Inferiority Tests for the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates
• Equivalence Tests for the Ratio of Two Poisson Rates
• Non-Inferiority Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Tests for the Ratio of Two Negative Binomial Rates
• Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
• Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
• Equivalence Tests for the Ratio of Two Negative Binomial Rates

Confidence Interval

• Confidence Intervals for the Difference Between Two Means
• Confidence Intervals for the Difference Between Two Means with Tolerance Probability

Non-Inferiority

• Two-Sample T-Tests for Non-Inferiority Assuming Equal Variance
• Two-Sample T-Tests for Non-Inferiority Allowing Unequal Variance
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Non-Inferiority
• Non-Inferiority Tests for the Ratio of Two Means (Log-Normal Data)
• Non-Inferiority Tests for the Ratio of Two Means (Normal Data)
• Non-Inferiority Tests for the Ratio of Two Poisson Rates
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Non-Inferiority Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates
• Non-Inferiority Tests for Two Means in a Cluster-Randomized Design
• Non-Inferiority Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Non-Inferiority
• Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Means (Simulation) (Legacy)
• Bridging Study using a Non-Inferiority Test of Two Groups (Continuous Outcome)

Superiority by a Margin

• Two-Sample T-Tests for Superiority by a Margin Assuming Equal Variance
• Two-Sample T-Tests for Superiority by a Margin Allowing Unequal Variance
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Superiority by a Margin
• Superiority by a Margin Tests for the Ratio of Two Means (Log-Normal Data)
• Superiority by a Margin Tests for the Ratio of Two Means (Normal Data)
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates
• Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Superiority by a Margin
• Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation)

Equivalence

• Two-Sample T-Tests for Equivalence Assuming Equal Variance
• Two-Sample T-Tests for Equivalence Allowing Unequal Variance
• Equivalence Tests for Two Means (Simulation)
• Equivalence Tests for the Ratio of Two Means (Normal Data)
• Equivalence Tests for the Ratio of Two Means (Log-Normal Data)
• Equivalence Tests for the Ratio of Two Poisson Rates
• Equivalence Tests for the Ratio of Two Negative Binomial Rates
• Equivalence Tests for Two Means in a Cluster-Randomized Design
• Bridging Study using the Equivalence Test of Two Groups (Continuous Outcome)

Biosimilar

• Biosimilarity Tests for the Difference Between Means using a Parallel Two-Group Design

Cluster-Randomized

• Tests for Two Means in a Cluster-Randomized Design
• Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm
• Tests for Two Means in a Stepped-Wedge Cluster-Randomized Design
• Non-Inferiority Tests for Two Means in a Cluster-Randomized Design
• Non-Inferiority Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm
• Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design
• Equivalence Tests for Two Means in a Cluster-Randomized Design
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-1 Randomization)
• GEE Tests for Two Means in a Cluster-Randomized Design
• GEE Tests for Two Means in a Stratified Cluster-Randomized Design
• Non-Inferiority Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design

Multicenter-Randomized

• Tests for Two Means in a Multicenter Randomized Design
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-1 Randomization)
• GEE Tests for Two Means in a Stratified Cluster-Randomized Design

Stratified

• GEE Tests for Two Means in a Stratified Cluster-Randomized Design
• Stratified Wilcoxon-Mann-Whitney (van Elteren) Test

Repeated Measures

• Tests for Two Means in a Repeated Measures Design
• Tests for Two Groups of Pre-Post Scores
• GEE Tests for Two Means in a Split-Mouth Design

Group-Sequential

• Group-Sequential Tests for Two Means with Known Variances (Simulation)
• Group-Sequential T-Tests for Two Means (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation)
• Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation)
• Group-Sequential Tests for Two Means (Legacy)
• Group-Sequential Tests for Two Means (Simulation) (Legacy)
• Group-Sequential Tests for Two Means Assuming Normality (Simulation) (Legacy)
• Group-Sequential Non-Inferiority Tests for Two Means (Simulation) (Legacy)

Multiple Testing

• Multiple Testing for Two Means

Conditional Power

• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Superiority by a Margin

Pilot Studies

• Pilot Study Sample Size Rules of Thumb
• UCL of the Standard Deviation from a Pilot Study
• Sample Size of a Pilot Study using the Upper Confidence Limit of the SD
• Sample Size of a Pilot Study using the Non-Central t to Allow for Uncertainty in the SD
• Required Sample Size to Detect a Problem in a Pilot Study

Bridging Studies

• Bridging Study using a Non-Inferiority Test of Two Groups (Continuous Outcome)
• Bridging Study using the Equivalence Test of Two Groups (Continuous Outcome)
• Bridging Study Test of Sensitivity using a Two-Group T-Test (Continuous Outcome)

Meta-Analysis

• Meta-Analysis of Tests for Two Means using a Fixed-Effects Model
• Meta-Analysis of Tests for Two Means using a Random-Effects Model

Two Means (Cluster-Randomized Design)

Test (Inequality)

• Tests for Two Means in a Cluster-Randomized Design
• Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm
• Tests for Two Means in a Stepped-Wedge Cluster-Randomized Design
• Tests for the Matched-Pair Difference of Two Means in a Cluster-Randomized Design
• GEE Tests for Two Means in a Cluster-Randomized Design

Non-Inferiority

• Non-Inferiority Tests for Two Means in a Cluster-Randomized Design
• Non-Inferiority Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm

Superiority by a Margin

• Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design

Equivalence

• Equivalence Tests for Two Means in a Cluster-Randomized Design

Mixed Models (2-Level Hierarchical Design)

• Mixed Models Tests for Two Means in a Cluster-Randomized Design
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Means at the End of Follow-Up in a 2-Level Hierarchical Design

Mixed Models (3-Level Hierarchical Design)

• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Means at the End of Follow-Up in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Fixed Slopes (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-2 Randomization)

GEE

• GEE Tests for Two Means in a Cluster-Randomized Design
• GEE Tests for Two Means in a Stratified Cluster-Randomized Design
• GEE Tests for Two Means in a Split-Mouth Design
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Continuous Outcome)

Stratified

• GEE Tests for Two Means in a Stratified Cluster-Randomized Design

Meta-Analysis

• Meta-Analysis of Tests for Two Means using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for Two Means using a Random-Effects Model in a Cluster-Randomized Design

Multiple Means (Cluster-Randomized Design)

Mixed Models (Interaction in a 2×2 Design)

• Mixed Models Tests for Interaction in a 2×2 Factorial 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-2 Randomization)

Mixed Models (Slope-Interaction in a 2×2 Design)

• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 2-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 2-Level Hierarchical Design with Random Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Fixed Slopes (Level-3 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Random Slopes (Level-2 Randomization)

GEE Tests for Multiple Groups

• GEE Tests for Multiple Means in a Cluster-Randomized Design
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Continuous Outcome)

Multi-Arm Tests vs. a Control

• Multi-Arm Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for Treatment and Control Means in a Cluster-Randomized Design

Cross-Over (2×2) Design

Test (Inequality)

• Tests for the Difference Between Two Means in a 2x2 Cross-Over Design
• Tests for the Ratio of Two Means in a 2x2 Cross-Over Design (Log-Normal Data)
• Conditional Power and Sample Size Reestimation of Tests for Two Means in a 2x2 Cross-Over Design
• Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design

Non-Inferiority

• Non-Inferiority Tests for the Difference Between Two Means in a 2x2 Cross-Over Design
• Non-Inferiority Tests for the Ratio of Two Means in a 2x2 Cross-Over Design (Log-Normal Data)
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design

Superiority by a Margin

• Superiority by a Margin Tests for the Difference Between Two Means in a 2x2 Cross-Over Design
• Superiority by a Margin Tests for the Ratio of Two Means in a 2x2 Cross-Over Design (Log-Normal Data)
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design

Equivalence

• Equivalence Tests for the Difference Between Two Means in a 2x2 Cross-Over Design
• Equivalence Tests for the Ratio of Two Means in a 2x2 Cross-Over Design (Log-Normal Data)
• Equivalence Tests for the Ratio of Two Means in a 2x2 Cross-Over Design (Normal Data)
• Bioequivalence Tests for AUC and Cmax in a 2x2 Cross-Over Design (Log-Normal Data)
• Equivalence Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design

Conditional Power

• Conditional Power and Sample Size Reestimation of Tests for Two Means in a 2x2 Cross-Over Design
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design

Cross-Over (Higher-Order) Design

Test (Inequality)

• Tests for the Difference of Two Means in a Higher-Order Cross-Over Design
• Tests for the Ratio of Two Means in a Higher-Order Cross-Over Design (Log-Normal Data)
• MxM Cross-Over Designs
• M-Period Cross-Over Designs using Contrasts

Non-Inferiority

• Non-Inferiority Tests for the Difference of Two Means in a Higher-Order Cross-Over Design
• Non-Inferiority Tests for the Ratio of Two Means in a Higher-Order Cross-Over Design (Log-Normal Data)

Superiority by a Margin

• Superiority by a Margin Tests for the Difference of Two Means in a Higher-Order Cross-Over Design
• Superiority by a Margin Tests for the Ratio of Two Means in a Higher-Order Cross-Over Design (Log-Normal Data)

Equivalence

• Equivalence Tests for the Difference of Two Means in a Higher-Order Cross-Over Design
• Equivalence Tests for the Ratio of Two Means in a Higher-Order Cross-Over Design (Log-Normal Data)

Cross-Over (Williams) Design

Test (Inequality)

• Tests for Pairwise Mean Differences in a Williams Cross-Over Design

Non-Inferiority

• Non-Inferiority Tests for Pairwise Mean Differences in a Williams Cross-Over Design

Superiority by a Margin

• Superiority by a Margin Tests for Pairwise Mean Differences in a Williams Cross-Over Design

Equivalence

• Equivalence Tests for Pairwise Mean Differences in a Williams Cross-Over Design

One-Way Designs

ANOVA F-Test

• One-Way Analysis of Variance Assuming Equal Variances (F-Tests)
• One-Way Analysis of Variance F-Tests (Simulation)
• One-Way Analysis of Variance F-Tests using Effect Size
• Power Comparison of Tests of Means in One-Way Designs (Simulation)
• Non-Zero Null Tests for One-Way Analysis of Variance Assuming Equal Variances

Welch's (Unequal Variances) F-Test

• One-Way Analysis of Variance Allowing Unequal Variances
• Equivalence Tests for One-Way Analysis of Variance Allowing Unequal Variances

Contrasts

• One-Way Analysis of Variance Contrasts Assuming Equal Variances
• One-Way Analysis of Variance Contrasts Allowing Unequal Variances
• Analysis of Covariance (ANCOVA) Contrasts
• One-Way Repeated Measures Contrasts
• Confidence Intervals for One-Way Repeated Measures Contrasts
• M-Period Cross-Over Designs using Contrasts

Multiple Comparisons

• Pair-Wise Multiple Comparisons (Simulation)
• Multiple Comparisons of Treatments vs. a Control (Simulation)
• Multiple Contrasts (Simulation)
• Multiple Comparisons
• Multi-Arm Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
• Multi-Arm Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
• Multi-Arm Non-Inferiority Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
• Multi-Arm Non-Inferiority Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
• Multi-Arm Superiority by a Margin Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
• Multi-Arm Superiority by a Margin Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
• Multi-Arm Equivalence Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
• Multi-Arm Equivalence Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
• Multi-Arm Tests for the Ratio of Treatment and Control Means (Normal Data)
• Multi-Arm Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
• Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Means (Normal Data)
• Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
• Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Means (Normal Data)
• Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
• Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Means (Normal Data)
• Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
• Multi-Arm Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for Treatment and Control Means in a Cluster-Randomized Design
• Williams' Test for the Minimum Effective Dose
• One-Way Analysis of Variance Contrasts Assuming Equal Variances
• One-Way Analysis of Variance Contrasts Allowing Unequal Variances
• Analysis of Covariance (ANCOVA) Contrasts
• One-Way Repeated Measures Contrasts
• Confidence Intervals for One-Way Repeated Measures Contrasts

Analysis of Covariance (ANCOVA)

• Analysis of Covariance (ANCOVA)
• Analysis of Covariance (ANCOVA) Contrasts
• Analysis of Covariance (ANCOVA) (Legacy)

Cross-Over Designs

• M-Period Cross-Over Designs using Contrasts
• Tests for the Difference of Two Means in a Higher-Order Cross-Over Design
• Tests for the Ratio of Two Means in a Higher-Order Cross-Over Design (Log-Normal Data)
• MxM Cross-Over Designs

Repeated Measures Designs

• One-Way Repeated Measures
• One-Way Repeated Measures Contrasts
• Confidence Intervals for One-Way Repeated Measures Contrasts
• MxM Cross-Over Designs

Three-Arm Designs

• Equivalence Tests for the Mean Ratio in a Three-Arm Trial (Normal Data) (Simulation)

Equivalence

• Equivalence Tests for One-Way Analysis of Variance Assuming Equal Variances
• Equivalence Tests for One-Way Analysis of Variance Allowing Unequal Variances
• Studentized Range Tests for Equivalence
• Equivalence Tests for the Mean Ratio in a Three-Arm Trial (Normal Data) (Simulation)

Non-Zero Null

• Non-Zero Null Tests for One-Way Analysis of Variance Assuming Equal Variances
• Non-Zero Null Studentized Range Tests

Non-Normal Data

• One-Way Analysis of Variance F-Tests (Simulation)
• Kruskal-Wallis Tests (Simulation)
• Terry-Hoeffding Normal-Scores Tests of Means (Simulation)
• Van der Waerden Normal Quantiles Tests of Means (Simulation)
• Power Comparison of Tests of Means in One-Way Designs (Simulation)
• Pair-Wise Multiple Comparisons (Simulation)
• Multiple Comparisons of Treatments vs. a Control (Simulation)
• Multiple Contrasts (Simulation)

Studentized Range Test

• Studentized Range Tests
• Studentized Range Tests for Equivalence
• Non-Zero Null Studentized Range Tests

Nonparametric

• Kruskal-Wallis Tests (Simulation)
• Terry-Hoeffding Normal-Scores Tests of Means (Simulation)
• Van der Waerden Normal Quantiles Tests of Means (Simulation)
• Power Comparison of Tests of Means in One-Way Designs (Simulation)
• Pair-Wise Multiple Comparisons (Simulation)
• Multiple Comparisons of Treatments vs. a Control (Simulation)

GEE

• GEE Tests for Multiple Means in a Cluster-Randomized Design
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for Two Means in a Split-Mouth Design

Multi-Factor Designs (ANOVA)

• Factorial Analysis of Variance
• Factorial Analysis of Variance using Effect Size
• 2x2 Factorial Analysis of Variance Allowing Unequal Variances
• Randomized Block Analysis of Variance
• Repeated Measures Analysis
• Mixed Models (Simulation)

Multiple Comparisons

Pair-Wise

• Pair-Wise Multiple Comparisons (Simulation)
• Multiple Comparisons

Treatments vs. a Control (Difference)

• Multiple Comparisons of Treatments vs. a Control (Simulation)
• Multiple Comparisons
• Multi-Arm Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
• Multi-Arm Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
• Multi-Arm Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
• Multi-Arm Non-Inferiority Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
• Multi-Arm Non-Inferiority Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
• Multi-Arm Superiority by a Margin Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
• Multi-Arm Equivalence Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
• Multi-Arm Equivalence Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance

Treatments vs. a Control (Ratio)

• Multi-Arm Tests for the Ratio of Treatment and Control Means (Normal Data)
• Multi-Arm Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
• Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Means (Normal Data)
• Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
• Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Means (Normal Data)
• Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
• Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Means (Normal Data)
• Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Means (Log-Normal Data)

Minimum Effective Dose (Williams' Test)

• Williams' Test for the Minimum Effective Dose

Contrasts

• Multiple Contrasts (Simulation)
• One-Way Analysis of Variance Contrasts Assuming Equal Variances
• One-Way Analysis of Variance Contrasts Allowing Unequal Variances
• Analysis of Covariance (ANCOVA) Contrasts
• One-Way Repeated Measures Contrasts
• Confidence Intervals for One-Way Repeated Measures Contrasts

Repeated Measures

• One-Way Repeated Measures Contrasts
• Confidence Intervals for One-Way Repeated Measures Contrasts

Analysis of Covariance (ANCOVA)

• Analysis of Covariance (ANCOVA)
• Analysis of Covariance (ANCOVA) Contrasts
• Analysis of Covariance (ANCOVA) (Legacy)

Repeated Measures

Repeated Measures

• Repeated Measures Analysis
• Tests for Two Means in a Repeated Measures Design
• Tests for Two Groups of Pre-Post Scores
• One-Way Repeated Measures
• One-Way Repeated Measures Contrasts
• Confidence Intervals for One-Way Repeated Measures Contrasts

Cross-Over Designs

• MxM Cross-Over Designs
• M-Period Cross-Over Designs using Contrasts
• Tests for the Difference of Two Means in a Higher-Order Cross-Over Design
• Tests for the Ratio of Two Means in a Higher-Order Cross-Over Design (Log-Normal Data)

Mixed Models

• Mixed Models (Simulation)
• Mixed Models Tests for the Slope Difference in a 2-Level Hierarchical Design with Fixed Slopes
• Mixed Models Tests for the Slope Difference in a 2-Level Hierarchical Design with Random Slopes
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Fixed Slopes (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)

GEE

• GEE Tests for Two Means in a Cluster-Randomized Design
• GEE Tests for Two Means in a Split-Mouth Design
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Count Outcome)

Single-Case (AB)ᴷ Designs

• Tests for the Difference Between Treatment and Control Means in a Balanced Single-Case (AB)ᴷ Design with Multiple Cases

Mixed Models

General

• Mixed Models (Simulation)

Two Means (Multicenter Randomized Design)

• Tests for Two Means in a Multicenter Randomized Design

Two Means (2-Level Hierarchical Design)

• Mixed Models Tests for Two Means in a Cluster-Randomized Design
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Means at the End of Follow-Up in a 2-Level Hierarchical Design

Two Means (3-Level Hierarchical Design)

• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Means at the End of Follow-Up in a 3-Level Hierarchical Design (Level-3 Randomization)

2×2 Factorial (2-Level Hierarchical Design)

• Mixed Models Tests for Interaction in a 2×2 Factorial 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 2-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 2-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 2-Level Hierarchical Design with Random Slopes (Level-2 Randomization)

2×2 Factorial (3-Level Hierarchical Design)

• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Fixed Slopes (Level-3 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Random Slopes (Level-2 Randomization)

Slope Difference (2-Level Hierarchical Design)

• Mixed Models Tests for the Slope Difference in a 2-Level Hierarchical Design with Fixed Slopes
• Mixed Models Tests for the Slope Difference in a 2-Level Hierarchical Design with Random Slopes

Slope Difference (3-Level Hierarchical Design)

• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Fixed Slopes (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-2 Randomization)

GEE

• GEE Tests for Two Means in a Cluster-Randomized Design
• GEE Tests for Two Means in a Stratified Cluster-Randomized Design
• GEE Tests for Two Means in a Split-Mouth Design
• GEE Tests for Multiple Means in a Cluster-Randomized Design
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Continuous Outcome)
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design

Multivariate Means

• Hotelling's One-Sample T²
• Hotelling's Two-Sample T²
• Multivariate Analysis of Variance (MANOVA)

Nonparametric

One Mean

• Tests for One Mean (Simulation)
• Wilcoxon Signed-Rank Tests
• Wilcoxon Signed-Rank Tests for Non-Inferiority
• Wilcoxon Signed-Rank Tests for Superiority by a Margin
• Multiple Testing for One Mean (One-Sample or Paired Data)
• Confidence Intervals for a Percentile of a Normal Distribution
• Confidence Intervals for a Percentile of a Normal Distribution using Assurance Probability
• Confidence Intervals for a Percentile of a Normal Distribution using Expected Width
• Confidence Intervals for Regression-Based Reference Limits using Assurance Probability
• Confidence Intervals for Regression-Based Reference Limits using Expected Relative Precision

Paired Means

• Tests for Paired Means (Simulation)
• Paired Wilcoxon Signed-Rank Tests
• Paired Wilcoxon Signed-Rank Tests for Non-Inferiority
• Paired Wilcoxon Signed-Rank Tests for Superiority by a Margin
• Equivalence Tests for Paired Means (Simulation)
• Multiple Testing for One Mean (One-Sample or Paired Data)
• Tests for Paired Means (Simulation) (Legacy)

Two Independent Means

• Tests for Two Means (Simulation)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Noether)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Guenther)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Simulation)
• Stratified Wilcoxon-Mann-Whitney (van Elteren) Test
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Non-Inferiority
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Superiority by a Margin
• Equivalence Tests for Two Means (Simulation)
• Tests for Two Groups Assuming a Two-Part Model
• Tests for Two Groups Assuming a Two-Part Model with Detection Limits
• Multiple Testing for Two Means

Single-Factor

• Kruskal-Wallis Tests (Simulation)
• Terry-Hoeffding Normal-Scores Tests of Means (Simulation)
• Van der Waerden Normal Quantiles Tests of Means (Simulation)
• Power Comparison of Tests of Means in One-Way Designs (Simulation)

Multiple Comparisons

• Pair-Wise Multiple Comparisons (Simulation)
• Multiple Comparisons of Treatments vs. a Control (Simulation)
• Multiple Contrasts (Simulation)

Meta-Analysis

• Meta-Analysis of Tests for Paired Means using a Fixed-Effects Model
• Meta-Analysis of Tests for Paired Means using a Random-Effects Model
• Meta-Analysis of Tests for Two Means using a Fixed-Effects Model
• Meta-Analysis of Tests for Two Means using a Random-Effects Model
• Meta-Analysis of Tests for Two Means using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for Two Means using a Random-Effects Model in a Cluster-Randomized Design

Assurance

• Assurance for Two-Sample T-Tests Assuming Equal Variance
• Assurance for Two-Sample T-Tests Allowing Unequal Variance
• Assurance for Two-Sample Z-Tests Assuming Equal Variance
• Assurance for Two-Sample T-Tests for Non-Inferiority Assuming Equal Variance
• Assurance for Two-Sample T-Tests for Superiority by a Margin Assuming Equal Variance
• Assurance for Two-Sample T-Tests for Equivalence Assuming Equal Variance
• Assurance for Two-Sample T-Tests for Non-Inferiority Allowing Unequal Variance
• Assurance for Two-Sample T-Tests for Superiority by a Margin Allowing Unequal Variance
• Assurance for Two-Sample T-Tests for Equivalence Allowing Unequal Variance
• Assurance for Tests for Two Means in a Cluster-Randomized Design
• Assurance for Non-Inferiority Tests for Two Means in a Cluster-Randomized Design
• Assurance for Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design
• Assurance for Equivalence Tests for Two Means in a Cluster-Randomized Design

Tools

• Data Simulator
• Standard Deviation of Means Calculator
• Standard Deviation Estimator
• Probability Calculator

Meta-Analysis

Means

Paired Means

• Meta-Analysis of Tests for Paired Means using a Fixed-Effects Model
• Meta-Analysis of Tests for Paired Means using a Random-Effects Model

Two Independent Means

• Meta-Analysis of Tests for Two Means using a Fixed-Effects Model
• Meta-Analysis of Tests for Two Means using a Random-Effects Model

Two Means (Cluster-Randomized Design)

• Meta-Analysis of Tests for Two Means using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for Two Means using a Random-Effects Model in a Cluster-Randomized Design

Proportions

Two Independent Proportions

• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Fixed-Effects Model
• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Random-Effects Model
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Fixed-Effects Model
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Random-Effects Model

Two Proportions (Cluster-Randomized Design)

• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Random-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Random-Effects Model in a Cluster-Randomized Design

Correlation

• Meta-Analysis of Correlation Tests using a Fixed-Effects Model
• Meta-Analysis of Correlation Tests using a Random-Effects Model

Method Comparison

• Bland-Altman Method for Assessing Agreement in Method Comparison Studies
• Exact Method for Assessing Agreement in Method Comparison Studies
• Deming Regression
• Confidence Intervals for the Bland-Altman Range of Agreement using Assurance Probability
• Confidence Intervals for the Bland-Altman Range of Agreement using Expected Half-Width

Microarray

• Multiple Testing for One Mean (One-Sample or Paired Data)
• Multiple Testing for Two Means
• Tests for Fold Change of Two Means (Log-Normal Data)
• Mendelian Randomization with a Binary Outcome

Mixed Models

Means

General

• Mixed Models (Simulation)

Two Means (Multicenter Randomized Design)

• Tests for Two Means in a Multicenter Randomized Design

Two Means (2-Level Hierarchical Design)

• Mixed Models Tests for Two Means in a Cluster-Randomized Design
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 2-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Means at the End of Follow-Up in a 2-Level Hierarchical Design

Two Means (3-Level Hierarchical Design)

• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Means in a 3-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Means at the End of Follow-Up in a 3-Level Hierarchical Design (Level-3 Randomization)

2×2 Factorial (2-Level Hierarchical Design)

• Mixed Models Tests for Interaction in a 2×2 Factorial 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 2-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 2-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 2-Level Hierarchical Design with Random Slopes (Level-2 Randomization)

2×2 Factorial (3-Level Hierarchical Design)

• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Interaction in a 2×2 Factorial 3-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Fixed Slopes (Level-3 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)
• Mixed Models Tests for Slope-Interaction in a 2×2 Factorial 3-Level Hierarchical Design with Random Slopes (Level-2 Randomization)

Slope Difference (2-Level Hierarchical Design)

• Mixed Models Tests for the Slope Difference in a 2-Level Hierarchical Design with Fixed Slopes
• Mixed Models Tests for the Slope Difference in a 2-Level Hierarchical Design with Random Slopes

Slope Difference (3-Level Hierarchical Design)

• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Fixed Slopes (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-3 Randomization)
• Mixed Models Tests for the Slope Difference in a 3-Level Hierarchical Design with Random Slopes (Level-2 Randomization)

Proportions

Two Proportions (2-Level Hierarchical Design)

• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-1 Randomization)

Two Proportions (3-Level Hierarchical Design)

• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-1 Randomization)

Non-Inferiority

Means

One Mean

• One-Sample Z-Tests for Non-Inferiority
• One-Sample T-Tests for Non-Inferiority
• Wilcoxon Signed-Rank Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Non-Inferiority
• Group-Sequential Non-Inferiority Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Non-Inferiority T-Tests for One Mean (Simulation)

Paired Means

• Paired Z-Tests for Non-Inferiority
• Paired T-Tests for Non-Inferiority
• Paired Wilcoxon Signed-Rank Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Non-Inferiority

Two Independent Means

• Two-Sample T-Tests for Non-Inferiority Assuming Equal Variance
• Two-Sample T-Tests for Non-Inferiority Allowing Unequal Variance
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Non-Inferiority
• Non-Inferiority Tests for the Ratio of Two Means (Log-Normal Data)
• Non-Inferiority Tests for the Ratio of Two Means (Normal Data)
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Non-Inferiority
• Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation)

Two Means (Cluster-Randomized)

• Non-Inferiority Tests for Two Means in a Cluster-Randomized Design

Multiple Comparisons

• Multi-Arm Non-Inferiority Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
• Multi-Arm Non-Inferiority Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
• Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Means (Normal Data)
• Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Means (Log-Normal Data)
• Multi-Arm Non-Inferiority Tests for Treatment and Control Means in a Cluster-Randomized Design

Cross-Over (2×2) Design

• Non-Inferiority Tests for the Difference Between Two Means in a 2x2 Cross-Over Design
• Non-Inferiority Tests for the Ratio of Two Means in a 2x2 Cross-Over Design (Log-Normal Data)
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design

Cross-Over (Higher-Order) Design

• Non-Inferiority Tests for the Difference of Two Means in a Higher-Order Cross-Over Design
• Non-Inferiority Tests for the Ratio of Two Means in a Higher-Order Cross-Over Design (Log-Normal Data)

Cross-Over (Williams) Design

• Non-Inferiority Tests for Pairwise Mean Differences in a Williams Cross-Over Design

Group-Sequential

• Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Means (Simulation) (Legacy)
• Group-Sequential Non-Inferiority Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Non-Inferiority T-Tests for One Mean (Simulation)
• Group-Sequential Non-Inferiority Tests for One Poisson Rate (Simulation)

Conditional Power

• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design

Proportions

One Proportion

• Non-Inferiority Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for One Proportion
• Group-Sequential Non-Inferiority Tests for One Proportion (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Proportion (Simulation)

Two Correlated (Paired) Proportions

• Non-Inferiority Tests for the Difference Between Two Correlated Proportions
• Non-Inferiority Tests for the Ratio of Two Correlated Proportions

Two Independent Proportions

• Non-Inferiority Tests for the Difference Between Two Proportions
• Non-Inferiority Tests for the Ratio of Two Proportions
• Non-Inferiority Tests for the Odds Ratio of Two Proportions
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Proportions
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Non-Inferiority Tests for Vaccine Efficacy with Extremely Low Incidence
• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Ratio of Two Means
• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Difference of Two Means
• Tests for Vaccine Efficacy with Extremely Low Incidence
• Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation)

Two Proportions (Cluster-Randomized)

• Non-Inferiority Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for the Ratio of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design

Multiple Proportions (Multi-Arm Tests vs. a Control)

• Multi-Arm Non-Inferiority Tests for the Difference Between Treatment and Control Proportions
• Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Proportions
• Multi-Arm Non-Inferiority Tests for the Odds Ratio of Treatment and Control Proportions
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions
• Multi-Arm Non-Inferiority Tests for the Difference of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design

Cross-Over (2×2) Design

• Non-Inferiority Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
• Non-Inferiority Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
• Non-Inferiority Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design

Cross-Over (Williams) Design

• Non-Inferiority Tests for Pairwise Proportion Differences in a Williams Cross-Over Design

Group-Sequential

• Group-Sequential Non-Inferiority Tests for One Proportion (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for the Ratio of Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for the Odds Ratio of Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for the Difference of Two Proportions (Simulation) (Legacy)

Conditional Power

• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Proportions

Vaccine Efficacy

• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy with Extremely Low Incidence
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions

Rates and Counts

• Non-Inferiority Tests for the Ratio of Two Poisson Rates
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
• Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
• Non-Inferiority Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates
• Group-Sequential Non-Inferiority Tests for One Poisson Rate (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Poisson Rates (Simulation)

Survival

• Non-Inferiority Logrank Tests
• Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
• Multi-Arm Non-Inferiority Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Non-Inferiority Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Non-Inferiority Tests for Vaccine Efficacy using the Hazard Ratio (Cox's Proportional Hazards Model)
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)
• Conditional Power and Sample Size Reestimation of Non-Inferiority Logrank Tests
• Group-Sequential Non-Inferiority Tests for Two Hazard Rates (Simulation)
• Group-Sequential Non-Inferiority Tests for One Hazard Rate (Simulation)

Variances

• Non-Inferiority Tests for the Ratio of Two Variances
• Non-Inferiority Tests for the Ratio of Two Within-Subject Variances in a Parallel Design
• Non-Inferiority Tests for the Ratio of Two Within-Subject Variances in a 2×2M Replicated Cross-Over Design
• Non-Inferiority Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Non-Inferiority Tests for Two Between Variances in a Replicated Design
• Non-Inferiority Tests for Two Between-Subject Variances in a 2×2M Replicated Cross-Over Design
• Non-Inferiority Tests for Two Total Variances in a Replicated Design
• Non-Inferiority Tests for Two Total Variances in a 2×2 Cross-Over Design
• Non-Inferiority Tests for Two Total Variances in a 2×2M Replicated Cross-Over Design

Assurance

• Assurance for Two-Sample T-Tests for Non-Inferiority Assuming Equal Variance
• Assurance for Two-Sample T-Tests for Non-Inferiority Allowing Unequal Variance
• Assurance for Non-Inferiority Tests for Two Means in a Cluster-Randomized Design
• Assurance for Non-Inferiority Tests for the Difference Between Two Proportions
• Assurance for Non-Inferiority Tests for the Ratio of Two Proportions
• Assurance for Non-Inferiority Tests for the Odds Ratio of Two Proportions
• Assurance for Non-Inferiority Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Assurance for Non-Inferiority Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Assurance for Non-Inferiority Tests for the Ratio of Two Poisson Rates
• Assurance for Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
• Assurance for Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions

Nonparametric

One Mean

• Tests for One Mean (Simulation)
• Wilcoxon Signed-Rank Tests
• Wilcoxon Signed-Rank Tests for Non-Inferiority
• Wilcoxon Signed-Rank Tests for Superiority by a Margin
• Multiple Testing for One Mean (One-Sample or Paired Data)
• Confidence Intervals for a Percentile of a Normal Distribution
• Confidence Intervals for a Percentile of a Normal Distribution using Assurance Probability
• Confidence Intervals for a Percentile of a Normal Distribution using Expected Width
• Confidence Intervals for Regression-Based Reference Limits using Assurance Probability
• Confidence Intervals for Regression-Based Reference Limits using Expected Relative Precision

Paired Means

• Tests for Paired Means (Simulation)
• Paired Wilcoxon Signed-Rank Tests
• Paired Wilcoxon Signed-Rank Tests for Non-Inferiority
• Paired Wilcoxon Signed-Rank Tests for Superiority by a Margin
• Equivalence Tests for Paired Means (Simulation)
• Multiple Testing for One Mean (One-Sample or Paired Data)
• Tests for Paired Means (Simulation) (Legacy)

Two Independent Means

• Tests for Two Means (Simulation)
• Tests for Two Ordered Categorical Variables (Proportional Odds)
• Tests for Two Ordered Categorical Variables (Non-Proportional Odds)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Noether)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Guenther)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Simulation)
• Stratified Wilcoxon-Mann-Whitney (van Elteren) Test
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Non-Inferiority
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Superiority by a Margin
• Equivalence Tests for Two Means (Simulation)
• Tests for Two Groups Assuming a Two-Part Model
• Tests for Two Groups Assuming a Two-Part Model with Detection Limits
• Multiple Testing for Two Means

Single-Factor

• Kruskal-Wallis Tests (Simulation)
• Terry-Hoeffding Normal-Scores Tests of Means (Simulation)
• Van der Waerden Normal Quantiles Tests of Means (Simulation)
• Power Comparison of Tests of Means in One-Way Designs (Simulation)

Multiple Comparisons

• Pair-Wise Multiple Comparisons (Simulation)
• Multiple Comparisons of Treatments vs. a Control (Simulation)

Correlation

• Spearman's Rank Correlation Tests (Simulation)
• Kendall's Tau-b Correlation Tests (Simulation)
• Power Comparison of Correlation Tests (Simulation)

Variances

• Brown-Forsythe Test of Variances (Simulation)
• Conover Test of Variances (Simulation)
• Power Comparison of Tests of Variances (Simulation)

Reference Intervals

• Nonparametric Reference Intervals for Non-Normal Data

Tolerance Intervals

• Tolerance Intervals for Any Data (Nonparametric)

Normality

• Normality Tests (Simulation)
• Confidence Intervals for a Percentile of a Normal Distribution
• Confidence Intervals for a Percentile of a Normal Distribution using Assurance Probability
• Confidence Intervals for a Percentile of a Normal Distribution using Expected Width

Pilot Studies

• Pilot Study Sample Size Rules of Thumb
• UCL of the Standard Deviation from a Pilot Study
• Sample Size of a Pilot Study using the Upper Confidence Limit of the SD
• Sample Size of a Pilot Study using the Non-Central t to Allow for Uncertainty in the SD
• Required Sample Size to Detect a Problem in a Pilot Study

Post-Marketing Surveillance

• Tests for One Poisson Rate with No Background Incidence (Post-Marketing Surveillance)
• Tests for One Poisson Rate with Known Background Incidence (Post-Marketing Surveillance)
• Tests for Two Poisson Rates with Background Incidence Estimated by the Control (Post-Marketing Surveillance)
• Tests for Two Poisson Rates in a Matched Case-Control Design (Post-Marketing Surveillance)

Proportions

One Proportion

Test (Inequality)

• Tests for One Proportion
• Tests for One Proportion using Effect Size
• Acceptance Sampling for Attributes with Optimum Number of Nonconformities
• Acceptance Sampling for Attributes with Zero Nonconformities
• Acceptance Sampling for Attributes with Fixed Nonconformities
• Reliability Demonstration Tests of One Proportion
• Reliability Demonstration Tests of One Proportion with Adverse Events
• Conditional Power and Sample Size Reestimation of Tests for One Proportion

Confidence Interval

• Confidence Intervals for One Proportion
• Confidence Intervals for One Proportion from a Finite Population
• Confidence Intervals for One Proportion in a Stratified Design
• Confidence Intervals for One Proportion in a Cluster-Randomized Design
• Confidence Intervals for One Proportion in a Stratified Cluster-Randomized Design

Non-Inferiority

• Non-Inferiority Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for One Proportion
• Group-Sequential Non-Inferiority Tests for One Proportion (Simulation)

Superiority by a Margin

• Superiority by a Margin Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for One Proportion
• Group-Sequential Superiority by a Margin Tests for One Proportion (Simulation)

Equivalence

• Equivalence Tests for One Proportion

Group-Sequential

• Group-Sequential Tests for One Proportion (Simulation)
• Group-Sequential Non-Inferiority Tests for One Proportion (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Proportion (Simulation)
• Group-Sequential Tests for One Proportion in a Fleming Design
• Single-Stage Phase II Clinical Trials
• Two-Stage Designs for Tests of One Proportion (Simon)
• Three-Stage Phase II Clinical Trials

Rare Events

• Reliability Demonstration Tests of One Proportion
• Reliability Demonstration Tests of One Proportion with Adverse Events

Conditional Power

• Conditional Power and Sample Size Reestimation of Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for One Proportion

Two Correlated (Paired) Proportions

Test (Inequality)

• Tests for Two Correlated Proportions (McNemar Test)
• Tests for Two Correlated Proportions in a Matched Case-Control Design
• Tests for Two Correlated Proportions with Incomplete Observations
• Tests for the Matched-Pair Difference of Two Proportions in a Cluster-Randomized Design
• Tests for the Odds Ratio in a Matched Case-Control Design with a Binary X
• Tests for the Odds Ratio in a Matched Case-Control Design with a Quantitative X
• GEE Tests for Two Correlated Proportions with Dropout

Non-Inferiority

• Non-Inferiority Tests for the Difference Between Two Correlated Proportions
• Non-Inferiority Tests for the Ratio of Two Correlated Proportions

Equivalence

• Equivalence Tests for the Difference Between Two Correlated Proportions
• Equivalence Tests for the Ratio of Two Correlated Proportions

Confidence Interval

• Confidence Intervals for the Difference Between Two Correlated Proportions

Two Independent Proportions

Test (Inequality)

• Tests for Two Proportions
• Tests for Two Proportions using Effect Size
• Fisher's Exact Test for Two Proportions
• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Ratio of Two Means
• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Difference of Two Means
• Tests for Vaccine Efficacy with Extremely Low Incidence
• Tests for Two Groups Assuming a Two-Part Model
• Tests for Two Groups Assuming a Two-Part Model with Detection Limits
• Conditional Power and Sample Size Reestimation of Tests for the Difference Between Two Proportions

Test (Non-Zero Null)

• Non-Zero Null Tests for the Difference Between Two Proportions
• Non-Unity Null Tests for the Ratio of Two Proportions
• Non-Unity Null Tests for the Odds Ratio of Two Proportions

Confidence Interval

• Confidence Intervals for the Difference Between Two Proportions
• Confidence Intervals for the Ratio of Two Proportions
• Confidence Intervals for the Odds Ratio of Two Proportions
• Confidence Intervals for the Odds Ratio of Two Proportions using an Unmatched Case-Control Design
• Confidence Intervals for Vaccine Efficacy using a Cohort Design
• Confidence Intervals for Vaccine Efficacy using an Unmatched Case-Control Design

Non-Inferiority

• Non-Inferiority Tests for the Difference Between Two Proportions
• Non-Inferiority Tests for the Ratio of Two Proportions
• Non-Inferiority Tests for the Odds Ratio of Two Proportions
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Proportions
• Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation)
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy with Extremely Low Incidence
• Bridging Study using a Non-Inferiority Test of Two Groups (Binary Outcome)

Superiority by a Margin

• Superiority by a Margin Tests for the Difference Between Two Proportions
• Superiority by a Margin Tests for the Ratio of Two Proportions
• Superiority by a Margin Tests for the Odds Ratio of Two Proportions
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Proportions
• Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation)
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy with Extremely Low Incidence

Equivalence

• Equivalence Tests for the Difference Between Two Proportions
• Equivalence Tests for the Ratio of Two Proportions
• Equivalence Tests for the Odds Ratio of Two Proportions
• Bridging Study using the Equivalence Test of Two Groups (Binary Outcome)

Repeated Measures

• Tests for Two Proportions in a Repeated Measures Design
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for Two Proportions in a Split-Mouth Design

Stratified (Cochran-Mantel-Haenszel Test)

• Tests for Two Proportions in a Stratified Design (Cochran-Mantel-Haenszel Test)
• Tests for Two Proportions in a Stratified Cluster-Randomized Design (Cochran-Mantel-Haenszel Test)

Group-Sequential

• Group-Sequential Tests for Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for the Ratio of Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for the Odds Ratio of Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for the Ratio of Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for the Odds Ratio of Two Proportions (Simulation)
• Group-Sequential Tests for Two Proportions (Legacy)
• Group-Sequential Tests for Two Proportions (Simulation) (Legacy)
• Group-Sequential Non-Inferiority Tests for the Difference of Two Proportions (Simulation) (Legacy)
• Group-Sequential Superiority by a Margin Tests for the Difference of Two Proportions (Simulation) (Legacy)

Conditional Power

• Conditional Power and Sample Size Reestimation of Tests for the Difference Between Two Proportions
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Proportions
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Proportions

Vaccine Efficacy

• Confidence Intervals for Vaccine Efficacy using a Cohort Design
• Confidence Intervals for Vaccine Efficacy using an Unmatched Case-Control Design
• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Ratio of Two Means
• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Difference of Two Means
• Tests for Vaccine Efficacy with Extremely Low Incidence
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy with Extremely Low Incidence
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy with Extremely Low Incidence

Meta-Analysis

• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Fixed-Effects Model
• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Random-Effects Model
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Fixed-Effects Model
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Random-Effects Model

Two Proportions (Cluster-Randomized Design)

Test (Inequality)

• Tests for Two Proportions in a Cluster-Randomized Design
• Tests for Two Proportions in a Cluster-Randomized Design with Clustering in Only One Arm
• Tests for Two Proportions in a Stepped-Wedge Cluster-Randomized Design
• Tests for the Matched-Pair Difference of Two Proportions in a Cluster-Randomized Design
• GEE Tests for Two Proportions in a Split-Mouth Design

Test (Non-Zero Null)

• Non-Zero Null Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Non-Unity Null Tests for the Ratio of Two Proportions in a Cluster-Randomized Design

Non-Inferiority

• Non-Inferiority Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design with Clustering in Only One Arm
• Non-Inferiority Tests for the Ratio of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design

Superiority by a Margin

• Superiority by a Margin Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design

Equivalence

• Equivalence Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Equivalence Tests for the Ratio of Two Proportions in a Cluster-Randomized Design

Mixed Models (2-Level Hierarchical Design)

• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-1 Randomization)

Mixed Models (3-Level Hierarchical Design)

• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-1 Randomization)

GEE

• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for Two Proportions in a Split-Mouth Design

Vaccine Efficacy

• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design

Meta-Analysis

• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Random-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Random-Effects Model in a Cluster-Randomized Design

Multiple Proportions

One-Way Designs

• Tests for Multiple Proportions in a One-Way Design

Correlated Proportions

• Tests for Multiple Correlated Proportions (McNemar-Bowker Test of Symmetry)

Multi-Arm Tests vs. a Control

• Multi-Arm Tests for Treatment and Control Proportions
• Multi-Arm Non-Inferiority Tests for the Difference Between Treatment and Control Proportions
• Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Proportions
• Multi-Arm Non-Inferiority Tests for the Odds Ratio of Treatment and Control Proportions
• Multi-Arm Superiority by a Margin Tests for the Difference Between Treatment and Control Proportions
• Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Proportions
• Multi-Arm Superiority by a Margin Tests for the Odds Ratio of Treatment and Control Proportions
• Multi-Arm Equivalence Tests for the Difference Between Treatment and Control Proportions
• Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Proportions
• Multi-Arm Equivalence Tests for the Odds Ratio of Treatment and Control Proportions
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions

Trend Tests

• Cochran-Armitage Test for Trend in Proportions

Simon Phase II Designs

• Randomized Phase II Selection Designs for Binary Data (Simon)

Ordered Categories

• Tests for Two Ordered Categorical Variables (Proportional Odds)
• Tests for Two Ordered Categorical Variables (Non-Proportional Odds)

Dose-Finding

• Dose-Finding using the Bayesian Continual Reassessment Method (CRM)

Multiple Proportions (Cluster-Randomized Designs)

• GEE Tests for Multiple Proportions in a Cluster-Randomized Design
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Binary Outcome)
• Multi-Arm Tests for Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for the Difference of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for the Difference of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for the Difference of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design

Cross-Over (2x2) Design

Test (Inequality)

• Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
• Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
• Tests for Two Correlated Proportions (McNemar Test)
• Tests for Two Correlated Proportions with Incomplete Observations
• GEE Tests for Two Correlated Proportions with Dropout
• Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design

Non-Inferiority

• Non-Inferiority Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
• Non-Inferiority Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
• Non-Inferiority Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design

Superiority by a Margin

• Superiority by a Margin Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
• Superiority by a Margin Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
• Superiority by a Margin Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design

Equivalence

• Equivalence Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
• Equivalence Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
• Equivalence Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design

Cross-Over (Williams) Design

Test (Inequality)

• Tests for Pairwise Proportion Differences in a Williams Cross-Over Design

Non-Inferiority

• Non-Inferiority Tests for Pairwise Proportion Differences in a Williams Cross-Over Design

Superiority by a Margin

• Superiority by a Margin Tests for Pairwise Proportion Differences in a Williams Cross-Over Design

Equivalence

• Equivalence Tests for Pairwise Proportion Differences in a Williams Cross-Over Design

Contingency Table (Chi-Square Tests)

• Chi-Square Tests
• Tests for Multiple Correlated Proportions (McNemar-Bowker Test of Symmetry)

Repeated Measures

• Tests for Two Proportions in a Repeated Measures Design
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for Two Proportions in a Split-Mouth Design
• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-1 Randomization)

GEE

• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for Two Correlated Proportions with Dropout
• GEE Tests for Two Proportions in a Split-Mouth Design
• GEE Tests for Multiple Proportions in a Cluster-Randomized Design

Mixed Models

Two Proportions (2-Level Hierarchical Design)

• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-1 Randomization)

Two Proportions (3-Level Hierarchical Design)

• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-1 Randomization)

Stratified

• Confidence Intervals for One Proportion in a Stratified Design
• Confidence Intervals for One Proportion in a Stratified Cluster-Randomized Design
• Tests for Two Proportions in a Stratified Design (Cochran-Mantel-Haenszel Test)
• Tests for Two Proportions in a Stratified Cluster-Randomized Design (Cochran-Mantel-Haenszel Test)

Trend

• Cochran-Armitage Test for Trend in Proportions

Vaccine Efficacy

• Confidence Intervals for Vaccine Efficacy using a Cohort Design
• Confidence Intervals for Vaccine Efficacy using an Unmatched Case-Control Design
• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Ratio of Two Means
• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Difference of Two Means
• Tests for Vaccine Efficacy with Extremely Low Incidence
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy with Extremely Low Incidence
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy with Extremely Low Incidence
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions

Ordered Categorical Data

• Tests for Two Ordered Categorical Variables (Proportional Odds)
• Tests for Two Ordered Categorical Variables (Non-Proportional Odds)
• Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design
• Non-Inferiority Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design
• Superiority by a Margin Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design
• Equivalence Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design
• Tests for Two Ordered Categorical Variables (Legacy)

Logistic Regression

Binary X (Wald Test)

• Tests for the Odds Ratio in Logistic Regression with One Binary X (Wald Test)
• Tests for the Odds Ratio in Logistic Regression with One Binary X and Other X's (Wald Test)
• Tests for the Odds Ratio in Logistic Regression with Two Binary X's (Wald Test)
• Tests for the Interaction Odds Ratio in Logistic Regression with Two Binary X's (Wald Test)
• Tests for Two Ordered Categorical Variables (Proportional Odds)
• Tests for Two Ordered Categorical Variables (Non-Proportional Odds)
• Logistic Regression (Legacy)

Binary X (Confidence Interval)

• Confidence Intervals for the Odds Ratio in Logistic Regression with One Binary X
• Confidence Intervals for the Odds Ratio in Logistic Regression with Two Binary X's
• Confidence Intervals for the Interaction Odds Ratio in Logistic Regression with Two Binary X's

Continuous X's (Wald Test)

• Tests for the Odds Ratio in Logistic Regression with One Normal X (Wald Test)
• Tests for the Odds Ratio in Logistic Regression with One Normal X and Other X's (Wald Test)
• Logistic Regression (Legacy)

Conditional Logistic Regression

• Tests for the Odds Ratio in a Matched Case-Control Design with a Binary X
• Tests for the Odds Ratio in a Matched Case-Control Design with a Quantitative X

GEE Logistic Regression

• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for Two Proportions in a Split-Mouth Design
• GEE Tests for Multiple Proportions in a Cluster-Randomized Design

Mixed-Effects Logistic Regression

• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-1 Randomization)

Ordinal Logistic Regression

• Tests for Two Ordered Categorical Variables (Proportional Odds)
• Tests for Two Ordered Categorical Variables (Non-Proportional Odds)

Mediation Analysis

• Tests of Mediation Effect in Logistic Regression

Multiple Groups

• Tests for Multiple Proportions in a One-Way Design
• GEE Tests for Multiple Proportions in a Cluster-Randomized Design
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Binary Outcome)

Kappa Rater Agreement

• Kappa Test for Agreement Between Two Raters
• Confidence Intervals for Kappa

Sensitivity and Specificity

• Tests for One-Sample Sensitivity and Specificity
• Confidence Intervals for One-Sample Sensitivity
• Confidence Intervals for One-Sample Specificity
• Confidence Intervals for One-Sample Sensitivity and Specificity
• Tests for Paired Sensitivities
• Tests for Two Independent Sensitivities
• Tests for Paired Specificities
• Tests for Two Independent Specificities

Bridging Studies

• Bridging Study using the Equivalence Test of Two Groups (Binary Outcome)
• Bridging Study using a Non-Inferiority Test of Two Groups (Binary Outcome)

Assurance

• Assurance for Tests for Two Proportions
• Assurance for Non-Zero Null Tests for the Difference Between Two Proportions
• Assurance for Non-Inferiority Tests for the Difference Between Two Proportions
• Assurance for Superiority by a Margin Tests for the Difference Between Two Proportions
• Assurance for Equivalence Tests for the Difference Between Two Proportions
• Assurance for Non-Unity Null Tests for the Ratio of Two Proportions
• Assurance for Non-Inferiority Tests for the Ratio of Two Proportions
• Assurance for Superiority by a Margin Tests for the Ratio of Two Proportions
• Assurance for Equivalence Tests for the Ratio of Two Proportions
• Assurance for Non-Unity Null Tests for the Odds Ratio of Two Proportions
• Assurance for Non-Inferiority Tests for the Odds Ratio of Two Proportions
• Assurance for Superiority by a Margin Tests for the Odds Ratio of Two Proportions
• Assurance for Equivalence Tests for the Odds Ratio of Two Proportions
• Assurance for Tests for Two Proportions in a Cluster-Randomized Design
• Assurance for Non-Zero Null Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Non-Inferiority Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Superiority by a Margin Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Equivalence Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Assurance for Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions

Meta-Analysis

• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Fixed-Effects Model
• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Random-Effects Model
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Fixed-Effects Model
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Random-Effects Model
• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Odds Ratio of Two Proportions using a Random-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Fixed-Effects Model in a Cluster-Randomized Design
• Meta-Analysis of Tests for the Risk Ratio of Two Proportions using a Random-Effects Model in a Cluster-Randomized Design

Tools

• Chi-Square Effect Size Estimator
• Odds Ratio and Proportions Conversion Tool
• Kappa Estimator
• Probability Calculator

Quality Control

• Acceptance Sampling for Attributes with Optimum Number of Nonconformities
• Acceptance Sampling for Attributes with Zero Nonconformities
• Acceptance Sampling for Attributes with Fixed Nonconformities
• Operating Characteristic Curves for Acceptance Sampling for Attributes
• Control Charts for Means (Simulation)
• Control Charts for Variability (Simulation)
• Confidence Intervals for Cp
• Confidence Intervals for Cpk

Rates and Counts

Test (Inequality)

• Tests for One Poisson Rate
• Tests for the Difference Between Two Poisson Rates
• Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design with Adjustment for Varying Cluster Sizes
• Tests for the Ratio of Two Poisson Rates (Zhu)
• Tests for the Ratio of Two Poisson Rates (Gu)
• Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
• Tests for Vaccine Efficacy with Extremely Low Incidence
• Tests for the Ratio of Two Negative Binomial Rates

Non-Inferiority

• Non-Inferiority Tests for the Ratio of Two Poisson Rates
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
• Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
• Non-Inferiority Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates
• Group-Sequential Non-Inferiority Tests for One Poisson Rate (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Poisson Rates (Simulation)

Superiority by a Margin

• Superiority by a Margin Tests for the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
• Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
• Superiority by a Margin Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates
• Group-Sequential Superiority by a Margin Tests for One Poisson Rate (Simulation)
• Group-Sequential Superiority by a Margin Tests for Two Poisson Rates (Simulation)

Equivalence

• Equivalence Tests for the Ratio of Two Poisson Rates
• Equivalence Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
• Equivalence Tests for the Ratio of Two Negative Binomial Rates

Cluster-Randomized Design

• Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design with Adjustment for Varying Cluster Sizes
• Non-Inferiority Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Tests for Two Poisson Rates in a Stepped-Wedge Cluster-Randomized Design
• Tests for the Matched-Pair Difference of Two Event Rates in a Cluster-Randomized Design
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design

Cross-Over (2×2) Designs

Test (Inequality)

• Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design

Non-Inferiority

• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design

Superiority by a Margin

• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design

Equivalence

• Equivalence Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design

GEE

• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design

One-Way Designs

• Tests for Multiple Poisson Rates in a One-Way Design

Poisson Regression

• Poisson Regression
• Tests for Multiple Poisson Rates in a One-Way Design
• Tests of Mediation Effect in Poisson Regression
• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design

Post-Marketing Surveillance

• Tests for One Poisson Rate with No Background Incidence (Post-Marketing Surveillance)
• Tests for One Poisson Rate with Known Background Incidence (Post-Marketing Surveillance)
• Tests for Two Poisson Rates with Background Incidence Estimated by the Control (Post-Marketing Surveillance)
• Tests for Two Poisson Rates in a Matched Case-Control Design (Post-Marketing Surveillance)

Poisson Rates

One Rate

• Tests for One Poisson Rate
• Tests for One Poisson Rate with No Background Incidence (Post-Marketing Surveillance)
• Tests for One Poisson Rate with Known Background Incidence (Post-Marketing Surveillance)
• Group-Sequential Tests for One Poisson Rate (Simulation)
• Group-Sequential Non-Inferiority Tests for One Poisson Rate (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Poisson Rate (Simulation)

Two Rates

• Tests for the Difference Between Two Poisson Rates
• Tests for the Ratio of Two Poisson Rates (Zhu)
• Tests for the Ratio of Two Poisson Rates (Gu)
• Tests for Vaccine Efficacy with Extremely Low Incidence
• Non-Inferiority Tests for the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates
• Equivalence Tests for the Ratio of Two Poisson Rates
• Tests for Two Poisson Rates with Background Incidence Estimated by the Control (Post-Marketing Surveillance)
• Tests for Two Poisson Rates in a Matched Case-Control Design (Post-Marketing Surveillance)
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Group-Sequential Tests for Two Poisson Rates (Simulation)

Two Rates (Cluster-Randomized Design)

• Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design with Adjustment for Varying Cluster Sizes
• Non-Inferiority Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Tests for Two Poisson Rates in a Stepped-Wedge Cluster-Randomized Design
• Tests for the Matched-Pair Difference of Two Event Rates in a Cluster-Randomized Design

Two Rates (2x2 Cross-Over Design)

• Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
• Non-Inferiority Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
• Equivalence Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design

Multiple Rates

• Tests for Multiple Poisson Rates in a One-Way Design

GEE (Repeated Measures Design)

• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design

Poisson Regression

• Poisson Regression
• Tests of Mediation Effect in Poisson Regression

Vaccine Efficacy

• Tests for Vaccine Efficacy with Extremely Low Incidence
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design

Negative Binomal Rates

• Tests for the Ratio of Two Negative Binomial Rates
• Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
• Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
• Equivalence Tests for the Ratio of Two Negative Binomial Rates
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates

Vaccine Efficacy

• Tests for Vaccine Efficacy with Extremely Low Incidence
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates

Assurance

• Assurance for Tests for the Difference Between Two Poisson Rates
• Assurance for Tests for the Ratio of Two Poisson Rates
• Assurance for Non-Inferiority Tests for the Ratio of Two Poisson Rates
• Assurance for Superiority by a Margin Tests for the Ratio of Two Poisson Rates
• Assurance for Equivalence Tests for the Ratio of Two Poisson Rates
• Assurance for Tests for the Ratio of Two Negative Binomial Rates
• Assurance for Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
• Assurance for Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
• Assurance for Equivalence Tests for the Ratio of Two Negative Binomial Rates

Regression

Simple Linear Regression

Simple Linear Regression

• Simple Linear Regression
• Simple Linear Regression using R²
• Non-Zero Null Tests for Simple Linear Regression
• Non-Zero Null Tests for Simple Linear Regression using ρ²
• Non-Inferiority Tests for Simple Linear Regression
• Superiority by a Margin Tests for Simple Linear Regression
• Equivalence Tests for Simple Linear Regression

Difference

• Tests for the Difference Between Two Linear Regression Slopes
• Tests for the Difference Between Two Linear Regression Intercepts

Confidence Interval

• Confidence Intervals for Linear Regression Slope

Multiple Regression

Multiple Regression

• Multiple Regression

Effect Size

• Multiple Regression using Effect Size

Analysis of Covariance (ANCOVA)

• Analysis of Covariance (ANCOVA)
• Analysis of Covariance (ANCOVA) Contrasts
• Analysis of Covariance (ANCOVA) (Legacy)

Mediation Analysis

• Tests of Mediation Effect using the Sobel Test
• Tests of Mediation Effect in Linear Regression
• Joint Tests of Mediation in Linear Regression with Continuous Variables

Cox Regression

Cox Regression

• Cox Regression

Mediation Analysis

• Tests of Mediation Effect in Cox Regression

Poisson Regression

Poisson Regression

• Poisson Regression

GEE Poisson Regression

• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the Slope of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Count Outcome)
• GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design

Mediation Analysis

• Tests of Mediation Effect in Poisson Regression

Multiple Groups

• Tests for Multiple Poisson Rates in a One-Way Design

Logistic Regression

Binary X (Wald Test)

• Tests for the Odds Ratio in Logistic Regression with One Binary X (Wald Test)
• Tests for the Odds Ratio in Logistic Regression with One Binary X and Other X's (Wald Test)
• Tests for the Odds Ratio in Logistic Regression with Two Binary X's (Wald Test)
• Tests for the Interaction Odds Ratio in Logistic Regression with Two Binary X's (Wald Test)
• Tests for Two Ordered Categorical Variables (Proportional Odds)
• Tests for Two Ordered Categorical Variables (Non-Proportional Odds)
• Logistic Regression (Legacy)

Binary X (Confidence Interval)

• Confidence Intervals for the Odds Ratio in Logistic Regression with One Binary X
• Confidence Intervals for the Odds Ratio in Logistic Regression with Two Binary X's
• Confidence Intervals for the Interaction Odds Ratio in Logistic Regression with Two Binary X's

Continuous X's (Wald Test)

• Tests for the Odds Ratio in Logistic Regression with One Normal X (Wald Test)
• Tests for the Odds Ratio in Logistic Regression with One Normal X and Other X's (Wald Test)
• Logistic Regression (Legacy)

Conditional Logistic Regression

• Tests for the Odds Ratio in a Matched Case-Control Design with a Binary X
• Tests for the Odds Ratio in a Matched Case-Control Design with a Quantitative X

GEE Logistic Regression

• GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Two Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Binary Outcome)
• GEE Tests for Multiple Proportions in a Cluster-Randomized Design

Mixed-Effects Logistic Regression

• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 2-Level Hierarchical Design (Level-1 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-3 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-2 Randomization)
• Mixed Models Tests for Two Proportions in a 3-Level Hierarchical Design (Level-1 Randomization)

Ordinal Logistic Regression

• Tests for Two Ordered Categorical Variables (Proportional Odds)
• Tests for Two Ordered Categorical Variables (Non-Proportional Odds)

Mediation Analysis

• Tests of Mediation Effect in Logistic Regression

Multiple Groups

• Tests for Multiple Proportions in a One-Way Design

Deming Regression

• Deming Regression

Mediation Analysis

• Tests of Mediation Effect using the Sobel Test
• Tests of Mediation Effect in Linear Regression
• Joint Tests of Mediation in Linear Regression with Continuous Variables
• Tests of Mediation Effect in Logistic Regression
• Tests of Mediation Effect in Poisson Regression
• Tests of Mediation Effect in Cox Regression

Probit Analysis

• Probit Analysis

Michaelis-Menten Parameters

• Confidence Intervals for Michaelis-Menten Parameters

Mendelian Randomization

• Mendelian Randomization with a Continuous Outcome
• Mendelian Randomization with a Binary Outcome

Reference Intervals

• Reference Intervals for Clinical and Lab Medicine

ROC

• Tests for One ROC Curve
• Tests for Two ROC Curves
• Confidence Intervals for the Area Under an ROC Curve

Sample Size Reestimation

Means

Test (Inequality)

• Conditional Power and Sample Size Reestimation of One-Sample T-Tests
• Conditional Power and Sample Size Reestimation of Paired T-Tests
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests
• Conditional Power and Sample Size Reestimation of Tests for Two Means in a 2x2 Cross-Over Design

Non-Inferiority

• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Non-Inferiority
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design

Superiority by a Margin

• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design

Proportions

Test (Inequality)

• Conditional Power and Sample Size Reestimation of Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Tests for the Difference Between Two Proportions

Non-Inferiority

• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Non-Inferiority Tests for Two Proportions

Superiority by a Margin

• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Proportions

Survival

Test (Inequality)

• Conditional Power and Sample Size Reestimation of Logrank Tests

Non-Inferiority

• Conditional Power and Sample Size Reestimation of Non-Inferiority Logrank Tests

Superiority by a Margin

• Conditional Power and Sample Size Reestimation of Superiority by a Margin Logrank Tests

Simulation

Data Simulator

• Data Simulator

Correlation

• Pearson's Correlation Tests (Simulation)
• Spearman's Rank Correlation Tests (Simulation)
• Kendall's Tau-b Correlation Tests (Simulation)
• Power Comparison of Correlation Tests (Simulation)

Means

One Mean

• Tests for One Mean (Simulation)

Paired Means

• Tests for Paired Means (Simulation)
• Equivalence Tests for Paired Means (Simulation)
• Tests for Paired Means (Simulation) (Legacy)

Two Independent Means

• Tests for Two Means (Simulation)
• Mann-Whitney U or Wilcoxon Rank-Sum Tests (Simulation)
• Equivalence Tests for Two Means (Simulation)

Many Means (ANOVA)

• One-Way Analysis of Variance F-Tests (Simulation)
• Kruskal-Wallis Tests (Simulation)
• Terry-Hoeffding Normal-Scores Tests of Means (Simulation)
• Van der Waerden Normal Quantiles Tests of Means (Simulation)
• Power Comparison of Tests of Means in One-Way Designs (Simulation)
• Pair-Wise Multiple Comparisons (Simulation)
• Multiple Comparisons of Treatments vs. a Control (Simulation)
• Multiple Contrasts (Simulation)
• Mixed Models (Simulation)
• Equivalence Tests for the Mean Ratio in a Three-Arm Trial (Normal Data) (Simulation)

Group-Sequential

• Group-Sequential Tests for One Mean with Known Variance (Simulation)
• Group-Sequential T-Tests for One Mean (Simulation)
• Group-Sequential Non-Inferiority Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Non-Inferiority T-Tests for One Mean (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for One Mean (Simulation)
• Group-Sequential Tests for Two Means with Known Variances (Simulation)
• Group-Sequential T-Tests for Two Means (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation)
• Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation)
• Group-Sequential Tests for Two Means (Simulation) (Legacy)
• Group-Sequential Tests for Two Means Assuming Normality (Simulation) (Legacy)
• Group-Sequential Non-Inferiority Tests for Two Means (Simulation) (Legacy)

Normality Tests

• Normality Tests (Simulation)

Proportions

• Group-Sequential Tests for One Proportion (Simulation)
• Group-Sequential Non-Inferiority Tests for One Proportion (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Proportion (Simulation)
• Group-Sequential Tests for Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for the Ratio of Two Proportions (Simulation)
• Group-Sequential Non-Inferiority Tests for the Odds Ratio of Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for the Ratio of Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for the Odds Ratio of Two Proportions (Simulation)
• Group-Sequential Tests for Two Proportions (Simulation) (Legacy)
• Group-Sequential Non-Inferiority Tests for the Difference of Two Proportions (Simulation) (Legacy)
• Group-Sequential Superiority by a Margin Tests for the Difference of Two Proportions (Simulation) (Legacy)

Quality Control

• Control Charts for Means (Simulation)
• Control Charts for Variability (Simulation)

Survival

• Two-Group Survival Comparison Tests (Simulation)
• Group-Sequential Tests for Two Hazard Rates (Simulation)
• Group-Sequential Tests for One Hazard Rate (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Hazard Rates (Simulation)
• Group-Sequential Superiority by a Margin Tests for Two Hazard Rates (Simulation)
• Group-Sequential Non-Inferiority Tests for One Hazard Rate (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Hazard Rate (Simulation)
• Group-Sequential Logrank Tests (Simulation) (Legacy)

Poisson Rates

• Group-Sequential Tests for One Poisson Rate (Simulation)
• Group-Sequential Non-Inferiority Tests for One Poisson Rate (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Poisson Rate (Simulation)
• Group-Sequential Tests for Two Poisson Rates (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Poisson Rates (Simulation)
• Group-Sequential Superiority by a Margin Tests for Two Poisson Rates (Simulation)

Variances

• Bartlett Test of Variances (Simulation)
• Levene Test of Variances (Simulation)
• Brown-Forsythe Test of Variances (Simulation)
• Conover Test of Variances (Simulation)
• Power Comparison of Tests of Variances (Simulation)

Stratified

• Confidence Intervals for One Mean in a Stratified Design
• Confidence Intervals for One Mean in a Stratified Cluster-Randomized Design
• Confidence Intervals for One Proportion in a Stratified Design
• Confidence Intervals for One Proportion in a Stratified Cluster-Randomized Design
• Tests for Two Proportions in a Stratified Design (Cochran-Mantel-Haenszel Test)
• Tests for Two Proportions in a Stratified Cluster-Randomized Design (Cochran-Mantel-Haenszel Test)
• GEE Tests for Two Means in a Stratified Cluster-Randomized Design
• Stratified Wilcoxon-Mann-Whitney (van Elteren) Test
• Tests for Two Groups using the Win-Ratio Composite Endpoint in a Stratified Design

Superiority by a Margin

Means

One Mean

• One-Sample Z-Tests for Superiority by a Margin
• One-Sample T-Tests for Superiority by a Margin
• Wilcoxon Signed-Rank Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Superiority by a Margin
• Group-Sequential Superiority by a Margin Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for One Mean (Simulation)

Paired Means

• Paired Z-Tests for Superiority by a Margin
• Paired T-Tests for Superiority by a Margin
• Paired Wilcoxon Signed-Rank Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Superiority by a Margin

Two Independent Means

• Two-Sample T-Tests for Superiority by a Margin Assuming Equal Variance
• Two-Sample T-Tests for Superiority by a Margin Allowing Unequal Variance
• Mann-Whitney U or Wilcoxon Rank-Sum Tests for Superiority by a Margin
• Superiority by a Margin Tests for the Ratio of Two Means (Log-Normal Data)
• Superiority by a Margin Tests for the Ratio of Two Means (Normal Data)
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Superiority by a Margin
• Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation)

Two Means (Cluster-Randomized)

• Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design

Multiple Comparisons

• Multi-Arm Superiority by a Margin Tests for the Difference Between Treatment and Control Means Assuming Equal Variance
• Multi-Arm Superiority by a Margin Tests for the Difference Between Treatment and Control Means Allowing Unequal Variance
• Multi-Arm Superiority by a Margin Tests for Treatment and Control Means in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Means (Normal Data)
• Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Means (Log-Normal Data)

Cross-Over (2x2) Design

• Superiority by a Margin Tests for the Difference Between Two Means in a 2x2 Cross-Over Design
• Superiority by a Margin Tests for the Ratio of Two Means in a 2x2 Cross-Over Design (Log-Normal Data)
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design

Cross-Over (Higher-Order) Design

• Superiority by a Margin Tests for the Difference of Two Means in a Higher-Order Cross-Over Design
• Superiority by a Margin Tests for the Ratio of Two Means in a Higher-Order Cross-Over Design (Log-Normal Data)

Cross-Over (Williams) Design

• Superiority by a Margin Tests for Pairwise Mean Differences in a Williams Cross-Over Design

One-Way Design (Studentized Range)

• Non-Zero Null Studentized Range Tests

Group-Sequential

• Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Mean with Known Variance (Simulation)
• Group-Sequential Superiority by a Margin T-Tests for One Mean (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Poisson Rate (Simulation)

Conditional Power

• Conditional Power and Sample Size Reestimation of One-Sample T-Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of Paired T-Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of Two-Sample T-Tests for Superiority by a Margin
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design

Proportions

One Proportion

• Superiority by a Margin Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for One Proportion
• Group-Sequential Superiority by a Margin Tests for One Proportion (Simulation)

Two Independent Proportions

• Superiority by a Margin Tests for the Difference Between Two Proportions
• Superiority by a Margin Tests for the Ratio of Two Proportions
• Superiority by a Margin Tests for the Odds Ratio of Two Proportions
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Proportions
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Superiority by a Margin Tests for Vaccine Efficacy with Extremely Low Incidence

Two Proportions (Cluster-Randomized)

• Superiority by a Margin Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design

Multiple Proportions (Multi-Arm Tests vs. a Control)

• Multi-Arm Superiority by a Margin Tests for the Difference Between Treatment and Control Proportions
• Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Proportions
• Multi-Arm Superiority by a Margin Tests for the Odds Ratio of Treatment and Control Proportions
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions
• Multi-Arm Superiority by a Margin Tests for the Difference of Treatment and Control Proportions in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design

Cross-Over (2x2) Design

• Superiority by a Margin Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
• Superiority by a Margin Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
• Superiority by a Margin Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design

Cross-Over (Williams) Design

• Superiority by a Margin Tests for Pairwise Proportion Differences in a Williams Cross-Over Design

Group-Sequential

• Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for the Ratio of Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for the Odds Ratio of Two Proportions (Simulation)
• Group-Sequential Superiority by a Margin Tests for the Difference of Two Proportions (Simulation) (Legacy)

Conditional Power

• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for One Proportion
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Tests for Two Proportions

Vaccine Efficacy

• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy with Extremely Low Incidence
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design

Rates and Counts

• Superiority by a Margin Tests for the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
• Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
• Superiority by a Margin Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates
• Group-Sequential Superiority by a Margin Tests for One Poisson Rate (Simulation)
• Group-Sequential Superiority by a Margin Tests for Two Poisson Rates (Simulation)

Survival

• Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
• Multi-Arm Superiority by a Margin Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Superiority by a Margin Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Superiority by a Margin Tests for Vaccine Efficacy using the Hazard Ratio (Cox's Proportional Hazards Model)
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Logrank Tests
• Group-Sequential Superiority by a Margin Tests for Two Hazard Rates (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Hazard Rate (Simulation)

Variances

• Superiority by a Margin Tests for the Ratio of Two Variances
• Superiority by a Margin Tests for the Ratio of Two Within-Subject Variances in a Parallel Design
• Superiority by a Margin Tests for the Ratio of Two Within-Subject Variances in a 2×2M Replicated Cross-Over Design
• Superiority by a Margin Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Superiority by a Margin Tests for Two Between Variances in a Replicated Design
• Superiority by a Margin Tests for Two Between-Subject Variances in a 2×2M Replicated Cross-Over Design
• Superiority by a Margin Tests for Two Total Variances in a Replicated Design
• Superiority by a Margin Tests for Two Total Variances in a 2×2 Cross-Over Design
• Superiority by a Margin Tests for Two Total Variances in a 2×2M Replicated Cross-Over Design

Assurance

• Assurance for Two-Sample T-Tests for Superiority by a Margin Assuming Equal Variance
• Assurance for Two-Sample T-Tests for Superiority by a Margin Allowing Unequal Variance
• Assurance for Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design
• Assurance for Superiority by a Margin Tests for the Difference Between Two Proportions
• Assurance for Superiority by a Margin Tests for the Ratio of Two Proportions
• Assurance for Superiority by a Margin Tests for the Odds Ratio of Two Proportions
• Assurance for Superiority by a Margin Tests for the Difference of Two Proportions in a Cluster-Randomized Design
• Assurance for Superiority by a Margin Tests for the Ratio of Two Poisson Rates
• Assurance for Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
• Assurance for Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Assurance for Superiority by a Margin Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Assurance for Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions

Survival

One Survival Curve

• One-Sample Logrank Tests Assuming a Weibull Model (Wu)
• One-Sample Tests of Weibull Hazard Rates
• One-Sample Cure Model Tests
• One-Sample Tests for Exponential Hazard Rate
• Confidence Intervals for the Weibull Shape Parameter
• Group-Sequential Tests for One Hazard Rate (Simulation)
• Group-Sequential Non-Inferiority Tests for One Hazard Rate (Simulation)
• Group-Sequential Superiority by a Margin Tests for One Hazard Rate (Simulation)

Two Survival Curves

Test (Inequality)

• Logrank Tests
• Logrank Tests (Freedman)
• Logrank Tests (Freedman) (Legacy)
• Logrank Tests (Lachin and Foulkes)
• Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Two-Group Survival Comparison Tests (Simulation)
• Logrank Tests Accounting for Competing Risks
• Logrank Tests in a Cluster-Randomized Design
• Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Conditional Power and Sample Size Reestimation of Logrank Tests

Non-Inferiority

• Non-Inferiority Logrank Tests
• Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Non-Inferiority Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Hazard Ratio (Cox's Proportional Hazards Model)
• Conditional Power and Sample Size Reestimation of Non-Inferiority Logrank Tests

Superiority by a Margin

• Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Superiority by a Margin Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Hazard Ratio (Cox's Proportional Hazards Model)
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Logrank Tests

Equivalence

• Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Equivalence Tests for the Difference of Two Hazard Rates Assuming an Exponential Model

Group-Sequential

• Group-Sequential Tests for Two Hazard Rates (Simulation)
• Group-Sequential Non-Inferiority Tests for Two Hazard Rates (Simulation)
• Group-Sequential Superiority by a Margin Tests for Two Hazard Rates (Simulation)
• Group-Sequential Logrank Tests (Legacy)
• Group-Sequential Logrank Tests (Simulation) (Legacy)

Competing Risks

• Logrank Tests Accounting for Competing Risks

Cluster-Randomized

• Logrank Tests in a Cluster-Randomized Design
• Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design

Conditional Power

• Conditional Power and Sample Size Reestimation of Logrank Tests
• Conditional Power and Sample Size Reestimation of Non-Inferiority Logrank Tests
• Conditional Power and Sample Size Reestimation of Superiority by a Margin Logrank Tests

Win Ratio

• Tests for Two Groups using the Win-Ratio Composite Endpoint
• Tests for Two Groups using the Win-Ratio Composite Endpoint in a Stratified Design

Multiple Survival Curves

• Multi-Arm Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
• Multi-Arm Non-Inferiority Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
• Multi-Arm Superiority by a Margin Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
• Multi-Arm Equivalence Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)
• Multi-Arm Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Superiority by a Margin Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Equivalence Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design

Cox Regression

• Cox Regression
• Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
• Multi-Arm Tests for Survival Curves using Cox's Proportional Hazards Model in a Cluster-Randomized Design
• Multi-Arm Non-Inferiority Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
• Multi-Arm Superiority by a Margin Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
• Multi-Arm Equivalence Tests for Treatment and Control Survival Curves using Cox's Proportional Hazards Model
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)
• Tests of Mediation Effect in Cox Regression

Exponential Means

• Tests for One Exponential Mean
• Tests for Two Exponential Means
• One-Sample Tests for Exponential Hazard Rate

Confidence Intervals

• Confidence Intervals for the Exponential Lifetime Mean
• Confidence Intervals for an Exponential Lifetime Percentile
• Confidence Intervals for Exponential Reliability
• Confidence Intervals for the Exponential Hazard Rate
• Confidence Intervals for the Weibull Shape Parameter

Probit Analysis

• Probit Analysis

Vaccine Efficacy

• Non-Inferiority Tests for Vaccine Efficacy using the Hazard Ratio (Cox's Proportional Hazards Model)
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)
• Superiority by a Margin Tests for Vaccine Efficacy using the Hazard Ratio (Cox's Proportional Hazards Model)
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)

Win Ratio

• Tests for Two Groups using the Win-Ratio Composite Endpoint
• Tests for Two Groups using the Win-Ratio Composite Endpoint in a Stratified Design

Assurance

• Assurance for Logrank Tests (Freedman)
• Assurance for Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Assurance for Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Assurance for Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Assurance for Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards Model
• Assurance for Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Assurance for Non-Inferiority Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Assurance for Superiority by a Margin Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Assurance for Equivalence Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
• Assurance for Logrank Tests in a Cluster-Randomized Design

Legacy Procedures

• Logrank Tests (Freedman) (Legacy)
• Logrank Tests (Lachin and Foulkes)

Tools

• Survival Parameter Conversion Tool
• Probability Calculator

Tolerance Intervals

• Tolerance Intervals for Normal Data
• Tolerance Intervals for Exponential Data
• Tolerance Intervals for Gamma Data
• Tolerance Intervals for Any Data (Nonparametric)
• Reliability Demonstration Tests of One Proportion
• Reliability Demonstration Tests of One Proportion with Adverse Events

Vaccine Efficacy

Means

• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Ratio of Two Means
• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Difference of Two Means

Proportions

• Confidence Intervals for Vaccine Efficacy using a Cohort Design
• Confidence Intervals for Vaccine Efficacy using an Unmatched Case-Control Design
• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Ratio of Two Means
• Tests for Vaccine Efficacy with Composite Efficacy Measure using the Difference of Two Means
• Tests for Vaccine Efficacy with Extremely Low Incidence
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy with Extremely Low Incidence
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy with Extremely Low Incidence
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Treatment and Control Proportions in a Cluster-Randomized Design

Rates and Counts

• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Poisson Rates in a Cluster-Randomized Design
• Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates
• Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Negative Binomial Rates

Survival

• Non-Inferiority Tests for Vaccine Efficacy using the Hazard Ratio (Cox's Proportional Hazards Model)
• Multi-Arm Non-Inferiority Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)
• Superiority by a Margin Tests for Vaccine Efficacy using the Hazard Ratio (Cox's Proportional Hazards Model)
• Multi-Arm Superiority by a Margin Tests for Vaccine Efficacy using Treatment vs. Control Hazard Ratios (Cox's Proportional Hazards Model)

Assurance

• Assurance for Non-Inferiority Tests for Vaccine Efficacy using the Ratio of Two Proportions
• Assurance for Superiority by a Margin Tests for Vaccine Efficacy using the Ratio of Two Proportions

Variances

One Standard Deviation

• Tests for One Variance
• Confidence Intervals for One Standard Deviation using Standard Deviation
• Confidence Intervals for One Standard Deviation using Relative Error
• Confidence Intervals for One Standard Deviation with Tolerance Probability

One Variance

• Tests for One Variance
• Confidence Intervals for One Variance using Variance
• Confidence Intervals for One Variance using Relative Error
• Confidence Intervals for One Variance with Tolerance Probability

Two Variances

• Tests for the Ratio of Two Variances
• Non-Unity Null Tests for the Ratio of Two Variances
• Non-Inferiority Tests for the Ratio of Two Variances
• Superiority by a Margin Tests for the Ratio of Two Variances
• Equivalence Tests for the Ratio of Two Variances
• Confidence Intervals for the Ratio of Two Variances using Variances
• Confidence Intervals for the Ratio of Two Variances using Relative Error

Many Variances

• Bartlett Test of Variances (Simulation)
• Levene Test of Variances (Simulation)
• Brown-Forsythe Test of Variances (Simulation)
• Conover Test of Variances (Simulation)
• Power Comparison of Tests of Variances (Simulation)

Within-Subject Variances

Parallel Design (Ratio of Two Variances)

• Tests for the Ratio of Two Within-Subject Variances in a Parallel Design
• Non-Unity Null Tests for the Ratio of Within-Subject Variances in a Parallel Design
• Non-Inferiority Tests for the Ratio of Two Within-Subject Variances in a Parallel Design
• Superiority by a Margin Tests for the Ratio of Two Within-Subject Variances in a Parallel Design
• Equivalence Tests for the Ratio of Two Within-Subject Variances in a Parallel Design

Parallel Design (Difference of Coefficients of Variation)

• Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Non-Zero Null Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Non-Inferiority Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Superiority by a Margin Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Equivalence Tests for the Difference of Two Within-Subject CV's in a Parallel Design

2×2M Replicated Cross-Over Design (Ratio of Two Variances)

• Tests for the Ratio of Two Within-Subject Variances in a 2×2M Replicated Cross-Over Design
• Non-Unity Null Tests for the Ratio of Within-Subject Variances in a 2×2M Replicated Cross-Over Design
• Non-Inferiority Tests for the Ratio of Two Within-Subject Variances in a 2×2M Replicated Cross-Over Design
• Superiority by a Margin Tests for the Ratio of Two Within-Subject Variances in a 2×2M Replicated Cross-Over Design
• Equivalence Tests for the Ratio of Two Within-Subject Variances in a 2×2M Replicated Cross-Over Design

Between-Subject Variances

Parallel Replicated Design

• Tests for Two Between Variances in a Replicated Design
• Non-Unity Null Tests for Two Between Variances in a Replicated Design
• Non-Inferiority Tests for Two Between Variances in a Replicated Design
• Superiority by a Margin Tests for Two Between Variances in a Replicated Design

2×2M Replicated Cross-Over Design

• Tests for Two Between-Subject Variances in a 2×2M Replicated Cross-Over Design
• Non-Unity Null Tests for Two Between-Subject Variances in a 2×2M Replicated Cross-Over Design
• Non-Inferiority Tests for Two Between-Subject Variances in a 2×2M Replicated Cross-Over Design
• Superiority by a Margin Tests for Two Between-Subject Variances in a 2×2M Replicated Cross-Over Design

Total Variances

Parallel Design

• Tests for the Ratio of Two Variances
• Non-Unity Null Tests for the Ratio of Two Variances
• Non-Inferiority Tests for the Ratio of Two Variances
• Superiority by a Margin Tests for the Ratio of Two Variances
• Equivalence Tests for the Ratio of Two Variances

Parallel Replicated Design

• Tests for Two Total Variances in a Replicated Design
• Non-Unity Null Tests for Two Total Variances in a Replicated Design
• Non-Inferiority Tests for Two Total Variances in a Replicated Design
• Superiority by a Margin Tests for Two Total Variances in a Replicated Design

2×2 Cross-Over Design

• Tests for Two Total Variances in a 2×2 Cross-Over Design
• Non-Unity Null Tests for Two Total Variances in a 2×2 Cross-Over Design
• Non-Inferiority Tests for Two Total Variances in a 2×2 Cross-Over Design
• Superiority by a Margin Tests for Two Total Variances in a 2×2 Cross-Over Design

2×2M Replicated Cross-Over Design

• Tests for Two Total Variances in a 2×2M Replicated Cross-Over Design
• Non-Unity Null Tests for Two Total Variances in a 2×2M Replicated Cross-Over Design
• Non-Inferiority Tests for Two Total Variances in a 2×2M Replicated Cross-Over Design
• Superiority by a Margin Tests for Two Total Variances in a 2×2M Replicated Cross-Over Design

Coefficients of Variation

• Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Non-Zero Null Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Non-Inferiority Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Superiority by a Margin Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Equivalence Tests for the Difference of Two Within-Subject CV's in a Parallel Design

Non-Inferiority

• Non-Inferiority Tests for the Ratio of Two Variances
• Non-Inferiority Tests for the Ratio of Two Within-Subject Variances in a Parallel Design
• Non-Inferiority Tests for the Ratio of Two Within-Subject Variances in a 2×2M Replicated Cross-Over Design
• Non-Inferiority Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Non-Inferiority Tests for Two Between Variances in a Replicated Design
• Non-Inferiority Tests for Two Between-Subject Variances in a 2×2M Replicated Cross-Over Design
• Non-Inferiority Tests for Two Total Variances in a Replicated Design
• Non-Inferiority Tests for Two Total Variances in a 2×2 Cross-Over Design
• Non-Inferiority Tests for Two Total Variances in a 2×2M Replicated Cross-Over Design

Superiority by a Margin

• Superiority by a Margin Tests for the Ratio of Two Variances
• Superiority by a Margin Tests for the Ratio of Two Within-Subject Variances in a Parallel Design
• Superiority by a Margin Tests for the Ratio of Two Within-Subject Variances in a 2×2M Replicated Cross-Over Design
• Superiority by a Margin Tests for the Difference of Two Within-Subject CV's in a Parallel Design
• Superiority by a Margin Tests for Two Between Variances in a Replicated Design
• Superiority by a Margin Tests for Two Between-Subject Variances in a 2×2M Replicated Cross-Over Design
• Superiority by a Margin Tests for Two Total Variances in a Replicated Design
• Superiority by a Margin Tests for Two Total Variances in a 2×2 Cross-Over Design
• Superiority by a Margin Tests for Two Total Variances in a 2×2M Replicated Cross-Over Design

Equivalence

• Equivalence Tests for the Ratio of Two Variances
• Equivalence Tests for the Ratio of Two Within-Subject Variances in a Parallel Design
• Equivalence Tests for the Ratio of Two Within-Subject Variances in a 2×2M Replicated Cross-Over Design
• Equivalence Tests for the Difference of Two Within-Subject CV's in a Parallel Design

Tools

• Probability Calculator
• Standard Deviation Estimator
• Standard Deviation of Means Calculator
• Odds Ratio and Proportions Conversion Tool
• Chi-Square Effect Size Estimator
• Kappa Estimator
• Survival Parameter Conversion Tool
• Randomization Lists
• Data Simulator
• Macro Command Center
• Installation Validation Tool for Installation Qualification (IQ)
• Procedure Validation Tool for Operational Qualification (OQ)
• Spreadsheets
• Macros

Plots

• Scatter Plots
• 3D Surface Plots
• 3D Surface Plots with Groups
• Histograms

References

• References