# List of Sample Size Procedures – Over 1100 Scenarios

**Assurance****Bland-Altman Method****Bridging Studies****Cluster-Randomized Designs****Conditional Power****Confidence Intervals****Correlation****Cross-Over Designs****Equivalence****Exponential Distribution Parameter Confidence Intervals****Group-Sequential Tests****Means - One****Means - Two Independent****Means - Two Correlated or Paired****Means - 2x2 Cross-Over Designs****Means - Higher-Order Cross-Over Designs****Means - Many (ANOVA)****Mediation Effects****Meta-Analysis****Michaelis-Menten Parameters****Mixed Models****Non-Inferiority****Nonparametric****Non-Zero and Non-Unity Null Tests****Normality Tests****Pilot Studies****Proportions - One****Proportions - Two Independent****Proportions - Correlated or Paired****Proportions - Cross-Over Designs****Proportions - Sensitivity and Specificity****Proportions - Many****Quality Control****Rates and Counts****Reference Intervals****Regression****ROC Curves****Sensitivity and Specificity****Single-Case (AB)K Designs****Superiority by a Margin Test****Survival Analysis****Tolerance Intervals****Two-Part Models****Variances and Standard Deviations****Win-Ratio Composite Endpoint****Bayesian Adjustment****Tools****Design of Experiments**

## Assurance - 52 Scenarios

Click here to see additional details about assurance procedures in PASS.- Assurance for Two-Sample T-Tests Assuming Equal Variance
- Assurance for Two-Sample Z-Tests Assuming Equal Variance
- Assurance for Two-Sample T-Tests Allowing Unequal 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 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-Unity Null Tests for the Odds Ratio of Two Proportions
- Assurance for Superiority by a Margin 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 Odds Ratio of Two Proportions
- Assurance for Non-Inferiority Tests for the Odds Ratio of 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 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 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
- 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
- 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 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

## Bland-Altman Method - 1 Scenario

- Bland-Altman Method for Assessing Agreement in Method Comparison Studies

## Bridging Studies - 6 Scenarios

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

## Cluster-Randomized Designs - 74 Scenarios

- Tests for Two Means from a Cluster-Randomized Design
- Tests for Two Means in a Stepped-Wedge Cluster-Randomized Design - Complete Design
- Tests for Two Means in a Stepped-Wedge Cluster-Randomized Design - Incomplete Design (Custom)
- Tests for the Matched-Pair Difference of Two Means in a Cluster-Randomized Design
- Non-Inferiority Tests for Two Means in a Cluster-Randomized Design
- Equivalence Tests for Two Means in a Cluster-Randomized Design
- Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design
- Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
- Tests for Two Poisson Rates in a Stepped-Wedge Cluster-Randomized Design - Complete Design
- Tests for Two Poisson Rates in a Stepped-Wedge Cluster-Randomized Design - Incomplete Design (Custom)
- Tests for the Matched-Pair Difference of Two Event Rates in a Cluster-Randomized Design
- Tests for Two Proportions in a Cluster-Randomized Design – Z Test (Pooled)
- Tests for Two Proportions in a Cluster-Randomized Design – Z Test (Unpooled)
- Tests for Two Proportions in a Cluster-Randomized Design – Likelihood Score Test
- Tests for Two Proportions in a Cluster-Randomized Design using Proportions
- Tests for Two Proportions in a Cluster-Randomized Design using Differences
- Tests for Two Proportions in a Cluster-Randomized Design using Ratios
- Tests for Two Proportions in a Stepped-Wedge Cluster-Randomized Design - Complete Design
- Tests for Two Proportions in a Stepped-Wedge Cluster-Randomized Design - Incomplete Design (Custom)
- Tests for the Matched-Pair Difference of Two Proportions in a Cluster-Randomized Design
- Equivalence Tests of Two Proportions in a Cluster-Randomized Design – Z Test (Pooled)
- Equivalence Tests of Two Proportions in a Cluster-Randomized Design – Z Test (Unpooled)
- Equivalence Tests of Two Proportions in a Cluster-Randomized Design – Likelihood Score Test
- Equivalence Tests of Two Proportions in a Cluster-Randomized Design using Proportions
- Equivalence Tests of Two Proportions in a Cluster-Randomized Design using Differences
- Equivalence Tests of Two Proportions in a Cluster-Randomized Design using Ratios
- Non-Inferiority Tests of Two Proportions in a Cluster-Randomized Design – Z Test (Pooled)
- Non-Inferiority Tests of Two Proportions in a Cluster-Randomized Design – Z Test (Unpooled)
- Non-Inferiority Tests of Two Proportions in a Cluster-Randomized Design – Likelihood Score Test
- Non-Inferiority Tests of Two Proportions in a Cluster-Randomized Design using Proportions
- Non-Inferiority Tests of Two Proportions in a Cluster-Randomized Design using Differences
- Non-Inferiority Tests of Two Proportions in a Cluster-Randomized Design using Ratios
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design – Z Test (Pooled)
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design – Z Test (Unpooled)
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design – Z Test (Pooled)
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design using Proportions
- 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
- GEE Tests for Two Means in a Stratified Cluster-Randomized Design
- GEE Tests for Two Means in a Cluster-Randomized Design
- GEE Tests for Multiple Means in a Cluster-Randomized Design
- GEE Tests for Multiple Proportions in a Cluster-Randomized Design
- GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design
- Tests for Two Proportions in a Stratified Cluster-Randomized Design (Cochran-Mantel-Haenszel Test)
- Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design with Adjustment for Varying Cluster Sizes
- Mixed Models Tests for Two Means in a Cluster-Randomized Design
- Multi-Arm Tests for Treatment and Control Proportions in a Cluster-Randomized Design
- Multi-Arm, Non-Inferiority Tests for Treatment and Control Proportions in a Cluster-Randomized Design
- 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 Equivalence 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 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 the Ratio 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 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
- Multi-Arm Tests for Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Multi-Arm Non-Inferiority Tests for Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Multi-Arm Superiority by a Margin Tests for Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Multi-Arm Equivalence Tests for Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Meta-Analysis of Means using a Fixed-Effects Model in a Cluster-Randomized Design
- Meta-Analysis of 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
- Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm
- Non-Inferiority Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm
- Tests for Two Proportions in a Cluster-Randomized Design with Clustering in Only One Arm
- Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design with Clustering in Only One Arm
- Tests for Two Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design

## Conditional Power - 23 Scenarios

- Conditional Power of One-Sample T-Tests
- Conditional Power of Two-Sample T-Tests
- Conditional Power of Two-Sample T-Tests – Unequal n’s
- Conditional Power of Paired T-Tests
- Conditional Power of 2x2 Cross-Over Designs
- Conditional Power of Logrank Tests
- Conditional Power of One-Proportion Tests
- Conditional Power of Two-Proportions Tests
- Conditional Power of Two-Proportions Tests – Unequal n’s
- Conditional Power of Two-Sample T-Tests for Non-Inferiority
- Conditional Power of Two-Sample T-Tests for Superiority by a Margin
- Conditional Power of Non-Inferiority Tests for the Difference Between Two Proportions
- Conditional Power of Superiority by a Margin Tests for the Difference Between Two Proportions
- Conditional Power of Non-Inferiority Logrank Tests
- Conditional Power of Superiority by a Margin Logrank Tests
- Conditional Power of Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design
- Conditional Power of Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design
- Conditional Power of One-Sample T-Tests for Non-Inferiority
- Conditional Power of One-Sample T-Tests for Superiority by a Margin
- Conditional Power of Paired T-Tests for Non-Inferiority
- Conditional Power of Paired T-Tests for Superiority by a Margin
- Conditional Power of Non-Inferiority Tests for One Proportion
- Conditional Power of Superiority by a Margin Tests for One Proportion

## Confidence Intervals - 101 Scenarios

- 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 Coefficient Alpha
- Confidence Intervals for Kappa
- Confidence Intervals for One Mean with Known Standard Deviation
- Confidence Intervals for One Mean with Sample Standard Deviation
- Confidence Intervals for One Mean with Tolerance Probability with Known Standard Deviation
- Confidence Intervals for One Mean with Tolerance Probability with Sample Standard Deviation
- 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 the Difference between Two Means Assuming Equal Standard Deviations
- Confidence Intervals for the Difference between Two Means Assuming Unequal Standard Deviations
- Confidence Intervals for the Difference between Two Means with Tolerance Probability with Known Standard Deviation
- Confidence Intervals for the Difference between Two Means with Tolerance Probability with Sample Standard Deviation
- Confidence Intervals for Paired Means with Known Standard Deviation
- Confidence Intervals for Paired Means with Sample Standard Deviation
- Confidence Intervals for Paired Means with Tolerance Probability with Known Standard Deviation
- Confidence Intervals for Paired Means with Tolerance Probability with Sample Standard Deviation
- Confidence Intervals for One-Way Repeated Measures Contrasts
- Confidence Intervals for One Proportion – Exact (Clopper-Pearson)
- Confidence Intervals for One Proportion – Score (Wilson)
- Confidence Intervals for One Proportion – Score (Continuity Correction)
- Confidence Intervals for One Proportion – Simple Asymptotic
- Confidence Intervals for One Proportion – Simple Asymptotic (Continuity Correction)
- 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 One-Sample Sensitivity
- Confidence Intervals for One-Sample Specificity
- Confidence Intervals for One-Sample Sensitivity and Specificity
- Confidence Intervals for Two Proportions – Score (Farrington & Manning)
- Confidence Intervals for Two Proportions – Score (Farrington & Manning) – Unequal n’s
- Confidence Intervals for Two Proportions – Score (Miettinen & Nurminen)*
- Confidence Intervals for Two Proportions – Score (Miettinen & Nurminen) – Unequal n’s
- Confidence Intervals for Two Proportions – Score with Skewness (Gart & Nam)
- Confidence Intervals for Two Proportions – Score with Skewness (Gart & Nam) – Unequal n’s
- Confidence Intervals for Two Proportions – Score (Wilson)
- Confidence Intervals for Two Proportions – Score (Wilson) – Unequal n’s
- Confidence Intervals for Two Proportions – Score with Continuity Correction (Wilson)
- Confidence Intervals for Two Proportions – Score with Continuity Correction (Wilson) – Unequal n’s
- Confidence Intervals for Two Proportions – Chi-Square with Continuity Correction (Yates)
- Confidence Intervals for Two Proportions – Chi-Square with Continuity Correction (Yates) – Unequal n’s
- Confidence Intervals for Two Proportions – Chi-Square (Pearson)
- Confidence Intervals for Two Proportions – Chi-Square (Pearson) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Score (Farrington & Manning)
- Confidence Intervals for Two Proportions using Ratios – Score (Farrington & Manning) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Score (Miettinen & Nurminen)
- Confidence Intervals for Two Proportions using Ratios – Score (Miettinen & Nurminen) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Score with Skewness (Gart & Nam)
- Confidence Intervals for Two Proportions using Ratios – Score with Skewness (Gart & Nam) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Logarithm (Katz)
- Confidence Intervals for Two Proportions using Ratios – Logarithm (Katz) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Logarithm + ½ (Walter)
- Confidence Intervals for Two Proportions using Ratios – Logarithm + ½ (Walter) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Fleiss
- Confidence Intervals for Two Proportions using Ratios – Fleiss – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Exact (Conditional)
- Confidence Intervals for Two Proportions using Odds Ratios – Exact (Conditional) – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Score (Farrington & Manning)
- Confidence Intervals for Two Proportions using Odds Ratios – Score (Farrington & Manning) – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Score (Miettinen & Nurminen)
- Confidence Intervals for Two Proportions using Odds Ratios – Score (Miettinen & Nurminen) – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Fleiss
- Confidence Intervals for Two Proportions using Odds Ratios – Fleiss – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Logarithm
- Confidence Intervals for Two Proportions using Odds Ratios – Logarithm – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Mantel-Haenszel
- Confidence Intervals for Two Proportions using Odds Ratios – Mantel-Haenszel – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Simple
- Confidence Intervals for Two Proportions using Odds Ratios – Simple – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Simple + 1/2
- Confidence Intervals for Two Proportions using Odds Ratios – Simple + 1/2 – Unequal n’s
- Confidence Intervals for the Odds Ratio in a Logistic Regression with One Binary Covariate
- Confidence Intervals for the Odds Ratio in a Logistic Regression with Two Binary Covariates
- Confidence Intervals for the Interaction Odds Ratio in a Logistic Regression with Two Binary Covariates
- Confidence Intervals for Linear Regression Slope
- Confidence Intervals for Michaelis-Menten Parameters
- 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 – Known Standard Deviation
- Confidence Intervals for One Standard Deviation with Tolerance Probability – Sample Standard Deviation
- Confidence Intervals for One Variance using Variance
- Confidence Intervals for One Variance using Relative Error
- Confidence Intervals for One Variance with Tolerance Probability – Known Variance
- Confidence Intervals for One Variance with Tolerance Probability – Sample Variance
- Confidence Intervals for the Ratio of Two Variances using Variances
- Confidence Intervals for the Ratio of Two Variances using Variances – Unequal n’s
- Confidence Intervals for the Ratio of Two Variances using Relative Error
- Confidence Intervals for the Ratio of Two Variances using Relative Error – Unequal n’s
- Confidence Intervals for the Exponential Lifetime Mean
- Confidence Intervals for the Exponential Hazard Rate
- Confidence Intervals for an Exponential Lifetime Percentile
- Confidence Intervals for Exponential Reliability
- Confidence Intervals for a Percentile of a Normal Distribution
- Confidence Intervals for the Area Under an ROC Curve
- Confidence Intervals for the Area Under an ROC Curve – Unequal n’s

## Correlation - 22 Scenarios

Click here to see additional details about correlation procedures in PASS.- Tests for Two Correlations
- Tests for Two Correlations – Unequal n’s
- Pearson’s Correlation Tests
- Pearson’s Correlation Tests with Simulation
- Spearman’s Rank Correlation Tests with Simulation
- Kendall’s Tau-b Correlation Tests with Simulation
- Point Biserial Correlation Tests
- Power Comparison of Correlation Tests with Simulation
- Confidence Intervals for Spearman’s Rank Correlation
- Confidence Intervals for Kendall’s Tau-b Correlation
- Confidence Intervals for Point Biserial Correlation
- Tests for One Coefficient (or Cronbach's) Alpha
- Tests for Two Coefficient (or Cronbach's) Alphas
- Tests for Two Coefficient (or Cronbach's) Alphas – Unequal n’s
- Confidence Intervals for Coefficient (or Cronbach's) Alpha
- Tests for Intraclass Correlation
- Confidence Intervals for Intraclass Correlation
- Kappa Test for Agreement Between Two Raters
- Confidence Intervals for Kappa
- Lin's Concordance Correlation Coefficient
- Meta-Analysis of Correlations using a Fixed-Effects Model
- Meta-Analysis of Correlations using a Random-Effects Model

## Cross-Over Designs - 56 Scenarios

- Tests for Two Means in a 2x2 Cross-Over Design using Differences
- Tests for Two Means in a 2x2 Cross-Over Design using Ratios
- 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
- M x M Cross-Over Designs
- M-Period Cross-Over Designs using Contrasts
- Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design using Differences
- Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design using Ratios
- Non-Inferiority Tests for Two Means in a Higher-Order Cross-Over Design using Differences
- Non-Inferiority Tests for Two Means in a Higher-Order Cross-Over Design using Ratios
- Equivalence Tests for Two Means in a 2x2 Cross-Over Design using Differences
- Equivalence Tests for Two Means in a 2x2 Cross-Over Design using Ratios
- Equivalence Tests for Two Means in a Higher-Order Cross-Over Design using Differences
- Equivalence Tests for Two Means in a Higher-Order Cross-Over Design using Ratios
- Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design using Differences
- Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design using Ratios
- Superiority by a Margin Tests for Two Means in a Higher-Order Cross-Over Design using Differences
- Superiority by a Margin Tests for Two Means in a Higher-Order Cross-Over Design using Ratios
- Conditional Power of 2x2 Cross-Over Designs
- Tests for the Odds Ratio 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
- Superiority by a Margin Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
- Equivalence Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
- Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
- Non-Inferiority Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
- Superiority by a Margin Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
- Equivalence Tests for the Difference of Two Proportions in a 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
- 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 Gen. 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 Pairwise Proportion Differences in a Williams Cross-Over Design
- Non-Inferiority Tests for Pairwise Proportion Differences in a Williams Cross-Over Design
- Superiority by a Margin Tests for Pairwise Proportion Differences in a Williams Cross-Over Design
- Equivalence Tests for Pairwise Proportion Differences in a Williams Cross-Over Design
- Tests for Pairwise Mean Differences in a Williams Cross-Over Design
- Non-Inferiority Tests for Pairwise Mean Differences in a Williams Cross-Over Design
- Superiority by a Margin Tests for Pairwise Mean Differences in a Williams Cross-Over Design
- Equivalence Tests for Pairwise Mean Differences in a Williams 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
- 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
- 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
- Bioequivalence Tests for AUC and Cmax in a 2x2 Cross-Over Design (Log-Normal Data)

## Equivalence - 86 Scenarios

- Equivalence Tests for Paired Means (Simulation) – T-Test
- Equivalence Tests for Paired Means (Simulation) – Wilcoxon Test
- Equivalence Tests for Paired Means (Simulation) – Sign Test
- Equivalence Tests for Paired Means (Simulation) – Bootstrap
- Equivalence Tests for Two Means using Differences
- Equivalence Tests for Two Means using Differences – Unequal n’s
- Equivalence Tests for Two Means using Ratios
- Equivalence Tests for the Ratio of Two Poisson Rates
- Equivalence Tests for the Ratio of Two Poisson Rates – Unequal n’s
- Equivalence Tests for the Ratio of Two Negative Binomial Rates
- Equivalence Tests for the Ratio of Two Negative Binomial Rates – Unequal n’s
- Equivalence Tests for the Difference Between Two Paired Means
- Equivalence Tests for Two Means using Ratios – Unequal n’s
- Equivalence Tests for Two Means (Simulation) – T-Test
- Equivalence Tests for Two Means (Simulation) – T-Test – Unequal n’s
- Equivalence Tests for Two Means (Simulation) – Welch Test
- Equivalence Tests for Two Means (Simulation) – Welch Test – Unequal n’s
- Equivalence Tests for Two Means (Simulation) – Trim T-Test
- Equivalence Tests for Two Means (Simulation) – Trim T-Test – Unequal n’s
- Equivalence Tests for Two Means (Simulation) – Trim Welch Test
- Equivalence Tests for Two Means (Simulation) – Trim Welch Test – Unequal n’s
- Equivalence Tests for Two Means (Simulation) – Mann-Whitney Test
- Equivalence Tests for Two Means (Simulation) – Mann-Whitney Test – Unequal n’s
- Equivalence Tests for Two Means in a 2x2 Cross-Over Design
- Equivalence Tests for Two Means in a 2x2 Cross-Over Design using Ratios
- Equivalence Tests for Two Means in a Higher-Order Cross-Over Design
- Equivalence Tests for Two Means in a Higher-Order Cross-Over Design using Ratios
- Equivalence Tests for Two Means in a Cluster-Randomized Design
- Equivalence Tests for One Proportion – Exact Test
- Equivalence Tests for One Proportion – Z Test using S(P0)
- Equivalence Tests for One Proportion – Z Test using S(P0) with Continuity Correction
- Equivalence Tests for One Proportion – Z Test using S(Phat)
- Equivalence Tests for One Proportion – Z Test using S(Phat) with Continuity Correction
- Equivalence Tests for Two Proportions – Z Test (Pooled)
- Equivalence Tests for Two Proportions – Z Test (Pooled) – Unequal n’s
- Equivalence Tests for Two Proportions – Z Test (Unpooled)
- Equivalence Tests for Two Proportions – Z Test (Unpooled) – Unequal n’s
- Equivalence Tests for Two Proportions – Z Test (Pooled) with Continuity Correction
- Equivalence Tests for Two Proportions – Z Test (Pooled) with Continuity Correction – Unequal n’s
- Equivalence Tests for Two Proportions – Z Test (Unpooled) with Continuity Correction
- Equivalence Tests for Two Proportions – Z Test (Unpooled) with Continuity Correction – Unequal n’s
- Equivalence Tests for Two Proportions – Likelihood Score (Farrington & Manning)
- Equivalence Tests for Two Proportions – Likelihood Score (Farrington & Manning) – Unequal n’s
- Equivalence Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen)
- Equivalence Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Equivalence Tests for Two Proportions – Likelihood Score (Gart & Nam)
- Equivalence Tests for Two Proportions – Likelihood Score (Gart & Nam) – Unequal n’s
- Equivalence Tests for Two Correlated Proportions
- Equivalence Tests for Two Correlated Proportions using Ratios
- Equivalence Tests for Two Proportions in a Cluster-Randomized Design
- Equivalence Tests for Two Proportions in a Cluster-Randomized Design – Unequal n’s
- Equivalence Tests for Two Proportions in a Cluster-Randomized Design using Ratios
- Equivalence Tests for Two Proportions in a Cluster-Randomized Design using Ratios – Unequal n’s
- Equivalence Tests for Two Survival Curves using Cox’s Proportional Hazards Model
- Equivalence Tests for Two Survival Curves using Cox’s Proportional Hazards Model – Unequal n’s
- Equivalence Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
- Equivalence Tests for the Difference of Two Hazard Rates Assuming an Exponential Model – Unequal n’s
- Equivalence Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
- Equivalence Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
- Equivalence Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
- Equivalence Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design
- Equivalence Tests for Pairwise Proportion Differences in a Williams Cross-Over Design
- Equivalence Tests for Pairwise Mean Differences in a Williams Cross-Over Design
- Equivalence Tests for Simple Linear Regression
- 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
- Equivalence Tests for the Ratio of Two Variances
- One-Sample Z-Tests for Equivalence
- Paired Z-Tests for Equivalence
- Two-Sample T-Tests for Equivalence Allowing Unequal Variance
- Bioequivalence Tests for AUC and Cmax in a 2x2 Cross-Over Design (Log-Normal Data)
- Multi-Arm, Equivalence Tests of the Difference Between Treatment and Control Proportions
- Multi-Arm, Equivalence Tests of the Ratio of Treatment and Control Proportions
- Multi-Arm, Equivalence Tests of the Odds Ratio of Treatment and Control Proportions
- Multi-Arm, Equivalence Tests of the Difference Between Treatment and Control Means Assuming Equal Variance
- Multi-Arm, Equivalence Tests of the Ratio of Treatment and Control Means Assuming Normal Data with Equal Variance
- Multi-Arm, Equivalence Tests of the Ratio of Treatment and Control Means Assuming Log-Normal Data
- Multi-Arm, Equivalence Tests of the Difference Between Treatment and Control Means Allowing Unequal Variances
- Multi-Arm, Equivalence Tests Comparing Treatment and Control Survival Curves Using the Cox's Proportional Hazards Model
- Multi-Arm Equivalence Tests for Treatment and Control Means 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 Equivalence Tests for Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Biosimilar Tests for the Difference Between Means using a Parallel, Two-Group Design

## Exponential Distribution Parameter Confidence Intervals - 4 Scenarios

- 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

## Group-Sequential Tests - 114 Scenarios

Click here to see additional details about group-sequential procedures in PASS.- Group-Sequential Tests for One Mean with Known Variance (Simulation)
- Group-Sequential 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 Tests for Two Proportions (Simulation)
- Group-Sequential Tests for Two Means
- Group-Sequential Tests for Two Means – Unequal n’s
- Group-Sequential Tests for Two Means (Simulation) Assuming Normality
- Group-Sequential Tests for Two Means (Simulation) Assuming Normality – Unequal n’s
- Group-Sequential Tests for Two Means (Simulation) General Assumptions
- Group-Sequential Tests for Two Means (Simulation) General Assumptions – Unequal n’s
- Group-Sequential Tests for Two Means (Simulation) General Assumptions – Mann-Whitney Test
- Group-Sequential Tests for Two Means (Simulation) General Assumptions – Mann-Whitney Test – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Means
- Group-Sequential Non-Inferiority Tests for Two Means – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Means – Mann-Whitney Test
- Group-Sequential Non-Inferiority Tests for Two Means – Mann-Whitney Test – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation) – Unequal n’s
- Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation)
- Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation) – Unequal n’s
- Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation)
- Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation) – Unequal n’s
- Group-Sequential Tests for One Proportion in a Fleming Design
- Group-Sequential Tests for Two Proportions
- Group-Sequential Tests for Two Proportions – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Pooled)
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Pooled) – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Unpooled)
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Unpooled) – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Mantel-Haenszel
- Group-Sequential Tests for Two Proportions (Simulation) – Mantel-Haenszel – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Fisher’s Exact
- Group-Sequential Tests for Two Proportions (Simulation) – Fisher’s Exact – Unequal n’s
- Group-Sequential Tests for Two Proportions using Differences (Simulation)
- Group-Sequential Tests for Two Proportions using Ratios (Simulation)
- Group-Sequential Tests for Two Proportions using Odds Ratios (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Pooled)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Pooled) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Unpooled)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Unpooled) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Gart & Nam)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Gart & Nam) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions using Differences (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions using Ratios (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions using Odds Ratios (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Gart & Nam)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Gart & Nam) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions using Differences (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Proportions using Ratios (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Proportions using Odds Ratios (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Unequal n’s
- Group-Sequential Logrank Tests of Two Survival Curves assuming Exponential Survival
- Group-Sequential Logrank Tests of Two Survival Curves assuming Proportional Hazards
- Group-Sequential Logrank Tests (Simulation)
- Group-Sequential Logrank Tests (Simulation) – Unequal n’s
- Group-Sequential Logrank Tests (Simulation) – Gehan-Wilcoxon
- Group-Sequential Logrank Tests (Simulation) – Gehan-Wilcoxon – Unequal n’s
- Group-Sequential Logrank Tests (Simulation) – Tarone-Ware
- Group-Sequential Logrank Tests (Simulation) – Tarone-Ware – Unequal n’s
- Group-Sequential Logrank Tests (Simulation) – Peto-Peto
- Group-Sequential Logrank Tests (Simulation) – Peto-Peto – Unequal n’s
- Group-Sequential Logrank Tests (Simulation) – Modified Peto-Peto
- Group-Sequential Logrank Tests (Simulation) – Modified Peto-Peto – Unequal n’s
- Group-Sequential Logrank Tests (Simulation) – Fleming-Harrington Custom Parameters
- Group-Sequential Logrank Tests (Simulation) – Fleming-Harrington Custom Parameters – Unequal n’s
- Group-Sequential Logrank Tests using Hazard Rates (Simulation)
- Group-Sequential Logrank Tests using Median Survival Times (Simulation)
- Group-Sequential Logrank Tests using Proportion Surviving (Simulation)
- Group-Sequential Logrank Tests using Mortality (Simulation)
- Group-Sequential Tests for Two Hazard Rates (Simulation)
- Group-Sequential Tests for Two Hazard Rates (Simulation) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Hazard Rates (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Hazard Rates (Simulation) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Hazard Rates (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Hazard Rates (Simulation) – Unequal n’s
- 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)
- 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)
- 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)

## Means - One - 39 Scenarios

Click here to see additional details about one mean procedures in PASS.- Tests for One Mean – T-Test
- Tests for One Mean – Z-Test
- Tests for One Mean – Wilcoxon Nonparametric Adjustment
- Tests for One Mean – (Simulation) – T-Test
- Tests for One Mean – (Simulation) – Wilcoxon Test
- Tests for One Mean – (Simulation) – Sign Test
- Tests for One Mean – (Simulation) – Bootstrap Test
- Tests for One Mean – (Simulation) – Exponential Mean Test
- Tests for One Exponential Mean with Replacement
- Tests for One Exponential Mean without Replacement
- Tests for One Mean using Effect Size
- Tests for One Poisson Mean
- Confidence Intervals for One Mean
- Confidence Intervals for One Mean – Known Standard Deviation
- Confidence Intervals for One Mean with Tolerance Probability
- Confidence Intervals for One Mean with Tolerance Probability – Known Standard Deviation
- 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
- Non-Inferiority Tests for One Mean
- Superiority by a Margin Tests for One Mean
- Multiple One-Sample T-Tests – False Discovery Rate
- Multiple One-Sample Z-Tests – False Discovery Rate
- Multiple One-Sample T-Tests – Experiment-wise Error Rate
- Multiple One-Sample Z-Tests – Experiment-wise Error Rate
- Conditional Power of One-Sample T-Tests
- Hotelling’s One-Sample T2
- Conditional Power of One-Sample T-Tests for Non-Inferiority
- Conditional Power of One-Sample T-Tests for Superiority by a Margin
- One-Sample T-Tests
- One-Sample Z-Tests
- One-Sample Z-Tests for Non-Inferiority
- One-Sample Z-Tests for Superiority by a Margin
- One-Sample Z-Tests for Equivalence
- Wilcoxon Signed-Rank Tests
- Wilcoxon Signed-Rank Tests for Non-Inferiority
- Wilcoxon Signed-Rank Tests for Superiority by a Margin
- Group-Sequential Tests for One Mean with Known Variance (Simulation)
- Group-Sequential T-Tests for One Mean (Simulation)

## Means - Two Correlated or Paired - 32 Scenarios

Click here to see additional details about paired means procedures in PASS.- Tests for Paired Means – T-Test
- Tests for Paired Means – Z-Test
- Tests for Paired Means (Simulation) – T-Test
- Tests for Paired Means (Simulation) – Wilcoxon Test
- Tests for Paired Means (Simulation) – Sign Test
- Tests for Paired Means (Simulation) – Bootstrap Test
- Tests for Paired Means using Effect Size
- Tests for the Matched-Pair Difference of Two Means in a Cluster-Randomized Design
- Tests for the Matched-Pair Difference of Two Event Rates in a Cluster-Randomized Design
- Confidence Intervals for Paired Means with Known Standard Deviation
- Confidence Intervals for Paired Means with Sample Standard Deviation
- Confidence Intervals for Paired Means with Tolerance Probability with Known Standard Deviation
- Confidence Intervals for Paired Means with Tolerance Probability with Sample Standard Deviation
- Superiority by a Margin Tests for Paired Means
- Equivalence Tests for Paired Means
- Non-Inferiority Tests for Paired Means
- Multiple Paired T-Tests
- Conditional Power of Paired T-Tests
- Paired T-Tests
- Paired T-Tests for Non-Inferiority
- Paired T-Tests for Superiority by a Margin
- Paired Z-Tests
- Paired Z-Tests for Non-Inferiority
- Paired Z-Tests for Superiority by a Margin
- Paired Z-Tests for Equivalence
- Paired Wilcoxon Signed-Rank Tests
- Paired Wilcoxon Signed-Rank Tests for Non-Inferiority
- Paired Wilcoxon Signed-Rank Tests for Superiority by a Margin
- Conditional Power of Paired T-Tests for Non-Inferiority
- Conditional Power of Paired T-Tests for Superiority by a Margin
- Meta-Analysis of Paired Means using a Fixed-Effects Model
- Meta-Analysis of Paired Means using a Random-Effects Model

## Means - Two Independent - 158 Scenarios

Click here to see additional details about two independent means procedures in PASS.- Two-Sample T-Tests Assuming Equal Variances
- Two-Sample T-Tests Assuming Equal Variances – Unequal n’s
- Two-Sample T-Tests Allowing Unequal Variances
- Two-Sample T-Tests Allowing Unequal Variances – Unequal n’s
- Tests for Two Means (Simulation) – T-Test
- Tests for Two Means (Simulation) – T-Test – Unequal n’s
- Tests for Two Means (Simulation) – Welch’s T-Test
- Tests for Two Means (Simulation) – Welch’s T-Test – Unequal n’s
- Tests for Two Means (Simulation) – Trimmed T-Test
- Tests for Two Means (Simulation) – Trimmed T-Test – Unequal n’s
- Tests for Two Means (Simulation) – Trimmed Welch’s T-Test
- Tests for Two Means (Simulation) – Trimmed Welch’s T-Test – Unequal n’s
- Two-Sample T-Tests using Effect Size
- Two-Sample T-Tests using Effect Size – Unequal n’s
- Mann-Whitney-Wilcoxon Tests (Simulation)
- Mann-Whitney-Wilcoxon Tests (Simulation) – Unequal n’s
- Two-Sample Z-Tests Assuming Equal Variances
- Two-Sample Z-Tests Assuming Equal Variances – Unequal n’s
- Two-Sample Z-Tests Allowing Unequal Variances
- Two-Sample Z-Tests Allowing Unequal Variances – Unequal n’s
- Tests for Two Means using Ratios
- Tests for Two Means using Ratios – Unequal n’s
- Tests for Two Exponential Means
- Tests for Two Exponential Means – Unequal n’s
- Tests for Two Poisson Means – MLE
- Tests for Two Poisson Means – MLE – Unequal n’s
- Tests for Two Poisson Means – CMLE
- Tests for Two Poisson Means – CMLE – Unequal n’s
- Tests for Two Poisson Means – Ln(MLE)
- Tests for Two Poisson Means – Ln(MLE) – Unequal n’s
- Tests for Two Poisson Means – Ln(CMLE)
- Tests for Two Poisson Means – Ln(CMLE) – Unequal n’s
- Tests for Two Poisson Means – Variance Stabilized
- Tests for Two Poisson Means – Variance Stabilized – Unequal n’s
- Tests for Two Poisson Rates in a Stepped-Wedge Cluster-Randomized Design - Complete Design
- Tests for Two Poisson Rates in a Stepped-Wedge Cluster-Randomized Design - Incomplete Design (Custom)
- Confidence Intervals for the Difference between Two Means Assuming Equal Standard Deviations
- Confidence Intervals for the Difference between Two Means Assuming Equal Standard Deviations – Unequal n’s
- Confidence Intervals for the Difference between Two Means Assuming Unequal Standard Deviations
- Confidence Intervals for the Difference between Two Means Assuming Unequal Standard Deviations – Unequal n’s
- Confidence Intervals for the Difference between Two Means with Tolerance Probability with Known Standard Deviation
- Confidence Intervals for the Difference between Two Means with Tolerance Probability with Known Standard Deviation – Unequal n’s
- Confidence Intervals for the Difference between Two Means with Tolerance Probability with Sample Standard Deviation
- Confidence Intervals for the Difference between Two Means with Tolerance Probability with Sample Standard Deviation – Unequal n’s
- Non-Inferiority Tests for Two Means using Differences
- Non-Inferiority Tests for Two Means using Differences – Unequal n’s
- Non-Inferiority Tests for Two Means using Ratios
- Non-Inferiority Tests for Two Means using Ratios – Unequal n’s
- Non-Inferiority Tests for the Ratio of Two Poisson Rates
- Non-Inferiority Tests for the Ratio of Two Poisson Rates – Unequal n’s
- Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
- Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates – Unequal n’s
- Non-Inferiority Tests for Two Means in a Cluster-Randomized Design
- Group-Sequential Tests for Two Means
- Group-Sequential Tests for Two Means – Unequal n’s
- Group-Sequential Tests for Two Means (Simulation) Assuming Normality
- Group-Sequential Tests for Two Means (Simulation) Assuming Normality – Unequal n’s
- Group-Sequential Tests for Two Means (Simulation) General Assumptions
- Group-Sequential Tests for Two Means (Simulation) General Assumptions – Unequal n’s
- Group-Sequential Tests for Two Means (Simulation) General Assumptions – Mann-Whitney Test
- Group-Sequential Tests for Two Means (Simulation) General Assumptions – Mann-Whitney Test – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Means
- Group-Sequential Non-Inferiority Tests for Two Means – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Means – Mann-Whitney Test
- Group-Sequential Non-Inferiority Tests for Two Means – Mann-Whitney Test – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation) – Unequal n’s
- Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation)
- Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation) – Unequal n’s
- Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation)
- Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation) – Unequal n’s
- Equivalence Tests for Two Means using Differences
- Equivalence Tests for Two Means using Differences – Unequal n’s
- Equivalence Tests for Two Means using Ratios
- Equivalence Tests for the Ratio of Two Poisson Rates
- Equivalence Tests for the Ratio of Two Poisson Rates – Unequal n’s
- Equivalence Tests for the Ratio of Two Negative Binomial Rates
- Equivalence Tests for the Ratio of Two Negative Binomial Rates – Unequal n’s
- Equivalence Tests for Two Means in a Cluster-Randomized Design
- Equivalence Tests for the Ratio of Two Means (Normal Data)
- Equivalence Tests for Two Means using Ratios – Unequal n’s
- Equivalence Tests for Two Means (Simulation) – T-Test
- Equivalence Tests for Two Means (Simulation) – T-Test – Unequal n’s
- Equivalence Tests for Two Means (Simulation) – Welch Test
- Equivalence Tests for Two Means (Simulation) – Welch Test – Unequal n’s
- Equivalence Tests for Two Means (Simulation) – Trim T-Test
- Equivalence Tests for Two Means (Simulation) – Trim T-Test – Unequal n’s
- Equivalence Tests for Two Means (Simulation) – Trim Welch Test
- Equivalence Tests for Two Means (Simulation) – Trim Welch Test – Unequal n’s
- Equivalence Tests for Two Means (Simulation) – Mann-Whitney Test
- Equivalence Tests for Two Means (Simulation) – Mann-Whitney Test – Unequal n’s
- Superiority by a Margin Tests for Two Means using Differences
- Superiority by a Margin Tests for Two Means using Differences – Unequal n’s
- Superiority by a Margin Tests for Two Means using Ratios
- Superiority by a Margin Tests for Two Means using Ratios – Unequal n’s
- Superiority by a Margin Tests for the Ratio of Two Poisson Rates
- Superiority by a Margin Tests for the Ratio of Two Poisson Rates – Unequal n’s
- Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
- Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates – Unequal n’s
- Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design
- Tests for Two Means from a Cluster-Randomized Design
- Tests for Two Means from a Cluster-Randomized Design – Unequal n’s
- Tests for Two Means in a Stepped-Wedge Cluster-Randomized Design - Complete Design
- Tests for Two Means in a Stepped-Wedge Cluster-Randomized Design - Incomplete Design (Custom)
- Tests for Two Means in a Multicenter Randomized Design
- Multiple Two-Sample T-Tests – False-Discovery Rate
- Multiple Two-Sample T-Tests – False-Discovery Rate – Unequal n’s
- Multiple Two-Sample T-Tests – Experiment-wise Error Rate
- Multiple Two-Sample T-Tests – Experiment-wise Error Rate – Unequal n’s
- Tests for Two Means from a Repeated Measures Design
- Tests for Two Means from a Repeated Measures Design – Unequal n’s
- Tests for Two Groups of Pre-Post Scores
- Tests for Two Groups of Pre-Post Scores – Unequal n’s
- Conditional Power of Two-Sample T-Tests
- Conditional Power of Two-Sample T-Tests – Unequal n’s
- Hotelling's Two-Sample T-Squared
- Hotelling's Two-Sample T-Squared – Unequal n’s
- Tests for Fold Change of Two Means
- 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)
- 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 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 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 the Slope Diff. in a 3-Level Hier. Design with Fixed Slopes (Level-2 Rand.)
- Mixed Models Tests for the Slope Diff. in a 3-Level Hier. Design with Random Slopes (Level-2 Rand.)
- Mixed Models Tests for the Slope Diff. in a 3-Level Hier. Design with Fixed Slopes (Level-3 Rand.)
- Mixed Models Tests for the Slope Diff. in a 3-Level Hier. Design with Random Slopes (Level-3 Rand.)
- Group-Sequential Tests for Two Means with Known Variances (Simulation)
- Group-Sequential T-Tests for Two Means (Simulation)
- Conditional Power of Two-Sample T-Tests for Non-Inferiority
- Conditional Power of Two-Sample T-Tests for Superiority by a Margin
- 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 Two Means at the End of Follow-Up in a 2-Level Hierarchical Design
- Two-Sample T-Tests for Non-Inferiority Assuming Equal Variance
- Two-Sample T-Tests for Non-Inferiority Allowing Unequal Variance
- Two-Sample T-Tests for Superiority by a Margin Assuming Equal Variance
- Two-Sample T-Tests for Superiority by a Margin Allowing Unequal Variance
- Two-Sample T-Tests for Equivalence Allowing Unequal Variance
- Mann-Whitney U or Wilcoxon Rank-Sum Tests
- Mann-Whitney U or Wilcoxon Rank-Sum Tests for Non-Inferiority
- Mann-Whitney U or Wilcoxon Rank-Sum Tests for Superiority by a Margin
- GEE Tests for Two Means in a Stratified Cluster-Randomized Design
- GEE Tests for Two Means in a Cluster-Randomized Design
- Tests for Two Means in a Split-Mouth Design
- Mixed Models Tests for Two Means in a Cluster-Randomized Design
- Meta-Analysis of Means using a Fixed-Effects Model
- Meta-Analysis of Means using a Random-Effects Model
- Meta-Analysis of Means using a Fixed-Effects Model in a Cluster-Randomized Design
- Meta-Analysis of Means using a Random-Effects Model in a Cluster-Randomized Design
- Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm

## Means - 2x2 Cross-Over Designs - 11 Scenarios

Click here to see additional details about cross-over designs for two means procedures in PASS.- Tests for Two Means in a 2x2 Cross-Over Design using Differences
- Tests for Two Means in a 2x2 Cross-Over Design using Ratios
- Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design using Differences
- Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design using Ratios
- Equivalence Tests for Two Means in a 2x2 Cross-Over Design using Differences
- Equivalence Tests for Two Means in a 2x2 Cross-Over Design using Ratios
- Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design using Differences
- Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design using Ratios
- Conditional Power of 2x2 Cross-Over Designs
- Conditional Power of Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design
- Conditional Power of Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design

## Means - Higher-Order Cross-Over Designs - 14 Scenarios

Click here to see additional details about higher-order cross-over designs for means procedures in PASS.- Non-Inferiority Tests for Two Means in a Higher-Order Cross-Over Design using Differences
- Non-Inferiority Tests for Two Means in a Higher-Order Cross-Over Design using Ratios
- Equivalence Tests for Two Means in a Higher-Order Cross-Over Design using Differences
- Equivalence Tests for Two Means in a Higher-Order Cross-Over Design using Ratios
- Superiority by a Margin Tests for Two Means in a Higher-Order Cross-Over Design using Differences
- Superiority by a Margin Tests for Two Means in a Higher-Order Cross-Over Design using Ratios
- 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
- M x M Cross-Over Designs
- M-Period Cross-Over Designs using Contrasts
- Tests for Pairwise Mean Differences in a Williams Cross-Over Design
- Non-Inferiority Tests for Pairwise Mean Differences in a Williams Cross-Over Design
- Superiority by a Margin Tests for Pairwise Mean Differences in a Williams Cross-Over Design
- Equivalence Tests for Pairwise Mean Differences in a Williams Cross-Over Design

## Means - Many (ANOVA) - 73 Scenarios

Click here to see additional details about multiple means procedures in PASS.- One-Way Analysis of Variance
- One-Way Analysis of Variance – Unequal n’s
- One-Way Analysis of Variance F-Tests (Simulation)
- One-Way Analysis of Variance F-Tests (Simulation) – Unequal n’s
- One-Way Analysis of Variance F-Tests using Effect Size
- One-Way Analysis of Variance F-Tests using Effect Size – Unequal n’s
- Power Comparison of Tests of Means in One-Way Designs (Simulation)
- Power Comparison of Tests of Means in One-Way Designs (Simulation) – Unequal n’s
- Analysis of Covariance (ANCOVA)
- One-Way Analysis of Variance Contrasts
- One-Way Analysis of Variance Contrasts
- Analysis of Covariance (ANCOVA) – Unequal n’s
- Kruskal-Wallis Tests (Simulation)
- Kruskal-Wallis Tests (Simulation) – Unequal n’s
- Terry-Hoeffding Normal-Scores Tests of Means (Simulation)
- Terry-Hoeffding Normal-Scores Tests of Means (Simulation) – Unequal n’s
- Van der Waerden Normal Quantiles Tests of Means (Simulation)
- Van der Waerden Normal Quantiles Tests of Means (Simulation) – Unequal n’s
- Pair-wise Multiple Comparisons (Simulation) – Tukey-Kramer
- Pair-wise Multiple Comparisons (Simulation) – Tukey-Kramer – Unequal n’s
- Pair-wise Multiple Comparisons (Simulation) – Kruskal-Wallis
- Pair-wise Multiple Comparisons (Simulation) – Kruskal-Wallis – Unequal n’s
- Pair-wise Multiple Comparisons (Simulation) – Games-Howell
- Pair-wise Multiple Comparisons (Simulation) – Games-Howell – Unequal n’s
- Multiple Comparisons of Treatments vs. a Control (Simulation) – Dunnett
- Multiple Comparisons of Treatments vs. a Control (Simulation) – Dunnett – Unequal n’s
- Multiple Comparisons of Treatments vs. a Control (Simulation) – Kruskal-Wallis
- Multiple Comparisons of Treatments vs. a Control (Simulation) – Kruskal-Wallis – Unequal n’s
- Multiple Comparisons – All Pairs – Tukey-Kramer
- Multiple Comparisons – All Pairs – Tukey-Kramer – Unequal n’s
- Multiple Comparisons – With Best – Hsu
- Multiple Comparisons – With Best – Hsu – Unequal n’s
- Multiple Comparisons – With Control – Dunnett
- Multiple Comparisons – With Control – Dunnett – Unequal n’s
- Multiple Contrasts (Simulation) – Dunn-Bonferroni
- Multiple Contrasts (Simulation) – Dunn-Bonferroni – Unequal n’s
- Multiple Contrasts (Simulation) – Dunn-Welch
- Multiple Contrasts (Simulation) – Dunn-Welch – Unequal n’s
- Williams Test for the Minimum Effective Dose
- Factorial Analysis of Variance
- Factorial Analysis of Variance using Effect Size
- Randomized Block Analysis of Variance
- Repeated Measures Analysis
- Repeated Measures Analysis – Unequal n’s
- One-Way Repeated Measures
- One-Way Repeated Measures Contrasts
- Confidence Intervals for One-Way Repeated Measures Contrasts
- MANOVA
- MANOVA – Unequal n’s
- Mixed Models
- Mixed Models – Unequal n’s
- 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)
- GEE Tests for Multiple Means in a Cluster-Randomized Design
- Multi-Arm Tests of the Difference Between Treatment and Control Means Assuming Equal Variance
- Multi-Arm, Non-Inferiority Tests of the Difference Between Treatment and Control Means Assuming Equal Variance
- Multi-Arm, Superiority by a Margin Tests of the Difference Between Treatment and Control Means Assuming Equal Variance
- Multi-Arm, Equivalence Tests of the Difference Between Treatment and Control Means Assuming Equal Variance
- Multi-Arm Tests of the Ratio of Treatment and Control Means Assuming Normal Data with Equal Variances
- Multi-Arm, Non-Inferiority Tests of the Ratio of Treatment and Control Means Assuming Normal Data with Equal Variances
- Multi-Arm, Superiority by a Margin Tests of the Ratio of Treatment and Control Means Assuming Normal Data with Equal Variance
- Multi-Arm, Equivalence Tests of the Ratio of Treatment and Control Means Assuming Normal Data with Equal Variance
- Multi-Arm Tests of the Ratio of Treatment and Control Means Assuming Log-Normal Data
- Multi-Arm, Non-Inferiority Tests of the Ratio of Treatment and Control Means Assuming Log-Normal Data
- Multi-Arm, Superiority by a Margin Tests of the Ratio of Treatment and Control Means Assuming Log-Normal Data
- Multi-Arm, Equivalence Tests of the Ratio of Treatment and Control Means Assuming Log-Normal Data
- Multi-Arm Tests of the Difference Between Treatment and Control Means Allowing Unequal Variances
- Multi-Arm, Non-Inferiority Tests of the Difference Between Treatment and Control Means Allowing Unequal Variances
- Multi-Arm, Superiority by a Margin Tests of the Difference Between Treatment and Control Means Allowing Unequal Variances
- Multi-Arm, Equivalence Tests of the Difference Between Treatment and Control Means Allowing Unequal Variances
- 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 Equivalence 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

## Mediation Effects - 6 Scenarios

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

## Meta-Analysis - 16 Scenarios

- Meta-Analysis of Means using a Fixed-Effects Model
- Meta-Analysis of Means using a Random-Effects Model
- Meta-Analysis of Paired Means using a Fixed-Effects Model
- Meta-Analysis of Paired Means using a Random-Effects Model
- Meta-Analysis of Means using a Fixed-Effects Model in a Cluster-Randomized Design
- Meta-Analysis of Means using a Random-Effects Model in a Cluster-Randomized Design
- Meta-Analysis of Correlations using a Fixed-Effects Model
- Meta-Analysis of Correlations using a Random-Effects Model
- 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

## Michaelis-Menten Parameters - 2 Scenarios

- Confidence Intervals for Michaelis-Menten Parameters
- Confidence Intervals for Michaelis-Menten Parameters – Unequal n’s

## Mixed Models - 29 Scenarios

- Mixed Models
- Mixed Models – Unequal n’s
- 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 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 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 the Slope Diff. in a 3-Level Hier. Design with Fixed Slopes (Level-2 Rand.)
- Mixed Models Tests for the Slope Diff. in a 3-Level Hier. Design with Random Slopes (Level-2 Rand.)
- Mixed Models Tests for the Slope Diff. in a 3-Level Hier. Design with Fixed Slopes (Level-3 Rand.)
- Mixed Models Tests for the Slope Diff. in a 3-Level Hier. Design with Random Slopes (Level-3 Rand.)
- 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 Two Means at the End of Follow-Up in a 2-Level Hierarchical Design
- 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 Two Means at the End of Follow-Up in a 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 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 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 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 2-Level Hierarchical Design with Fixed Slopes (Level-2 Randomization)
- Mixed Models Tests for Two Means in a Cluster-Randomized Design

## Non-Inferiority - 115 Scenarios

- Non-Inferiority Tests for One Mean
- Non-Inferiority Tests for Two Means using Differences
- Non-Inferiority Tests for Two Means using Differences – Unequal n’s
- Non-Inferiority Tests for Two Means using Ratios
- Non-Inferiority Tests for Two Means using Ratios – Unequal n’s
- Non-Inferiority Tests for the Ratio of Two Poisson Rates
- Non-Inferiority Tests for the Ratio of Two Poisson Rates – Unequal n’s
- Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
- Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Means
- Group-Sequential Non-Inferiority Tests for Two Means – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Means – Mann-Whitney Test
- Group-Sequential Non-Inferiority Tests for Two Means – Mann-Whitney Test – Unequal n’s
- Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design using Differences
- Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design using Ratios
- Non-Inferiority Tests for Two Means in a Higher-Order Cross-Over Design using Differences
- Non-Inferiority Tests for Two Means in a Higher-Order Cross-Over Design using Ratios
- Non-Inferiority Tests for Two Means in a Cluster-Randomized Design
- Non-Inferiority Tests for One Proportion – Exact
- Non-Inferiority Tests for One Proportion – Z-Test using S(P0)
- Non-Inferiority Tests for One Proportion – Z-Test using S(P0) with Continuity Correction
- Non-Inferiority Tests for One Proportion – Z-Test using S(Phat)
- Non-Inferiority Tests for One Proportion – Z-Test using S(Phat) with Continuity Correction
- Non-Inferiority Tests for One Proportion using Differences
- Non-Inferiority Tests for One Proportion using Ratios
- Non-Inferiority Tests for One Proportion using Odds Ratios
- Non-Inferiority Tests for Two Proportions – Z-Test (Pooled)
- Non-Inferiority Tests for Two Proportions – Z-Test (Pooled) – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Z-Test (Unpooled)
- Non-Inferiority Tests for Two Proportions – Z-Test (Unpooled) – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Z-Test (Pooled) with Continuity Correction
- Non-Inferiority Tests for Two Proportions – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Z-Test (Unpooled) with Continuity Correction
- Non-Inferiority Tests for Two Proportions – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Farrington & Manning)
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Farrington & Manning) – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen)
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Gart & Nam)
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Gart & Nam) – Unequal n’s
- Non-Inferiority Tests for Two Proportions using Differences
- Non-Inferiority Tests for Two Proportions using Ratios
- Non-Inferiority Tests for Two Proportions using Odds Ratios
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Gart & Nam)
- Group-Sequential Non-Inferiority Tests for Two Proportions using Differences (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions using Ratios (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions using Odds Ratios (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Hazard Rates (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Hazard Rates (Simulation) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Means with Known Variances (Simulation) – Unequal n’s
- Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation)
- Group-Sequential Non-Inferiority T-Tests for Two Means (Simulation) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Unequal n’s
- Non-Inferiority Tests for Two Correlated Proportions using Differences
- Non-Inferiority Tests for Two Correlated Proportions using Ratios
- Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design – Z-Test (Pooled)
- Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design – Z-Test (Pooled) – Unequal n’s
- Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design – Z-Test (Unpooled)
- Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design – Z-Test (Unpooled) – Unequal n’s
- Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design – Likelihood Score (Farrington & Manning)
- Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design – Likelihood Score (Farrington & Manning) – Unequal n’s
- Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design using Differences
- Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design using Ratios
- 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 – Unequal n’s
- Non-Inferiority Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
- Non-Inferiority Tests for the Difference of Two Hazard Rates Assuming an Exponential Model – Unequal n’s
- Non-Inferiority Logrank Tests
- Non-Inferiority Logrank Tests – Unequal n’s
- Non-Inferiority Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
- Non-Inferiority Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
- Non-Inferiority Tests for the Ratio of Two Poisson Rates in a 2x2 Cross-Over Design
- Non-Inferiority Tests for the Generalized Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design
- Non-Inferiority Tests for Pairwise Proportion Differences in a Williams Cross-Over Design
- Non-Inferiority Tests for Pairwise Mean Differences in a Williams Cross-Over Design
- Conditional Power of Two-Sample T-Tests for Non-Inferiority
- Conditional Power of Non-Inferiority Tests for the Difference Between Two Proportions
- Conditional Power of Non-Inferiority Logrank Tests
- Conditional Power of Non-Inferiority Tests for Two Means in a 2x2 Cross-Over Design
- Conditional Power of One-Sample T-Tests for Non-Inferiority
- Conditional Power of Paired T-Tests for Non-Inferiority
- Conditional Power of Non-Inferiority Tests for One Proportion
- Non-Inferiority Tests for Simple Linear Regression
- 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 the Ratio of Two Variances
- 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 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 Between Variances in a Replicated Design
- One-Sample Z-Tests for Non-Inferiority
- Wilcoxon Signed-Rank Tests for Non-Inferiority
- Paired T-Tests for Non-Inferiority
- Paired Z-Tests for Non-Inferiority
- Paired Wilcoxon Signed-Rank Tests for Non-Inferiority
- Two-Sample T-Tests for Non-Inferiority Allowing Unequal Variance
- Two-Sample T-Tests for Non-Inferiority Assuming Equal Variance
- Mann-Whitney U or Wilcoxon Rank-Sum Tests for Non-Inferiority
- Multi-Arm, Non-Inferiority Tests of the Difference Between Treatment and Control Proportions
- Multi-Arm, Non-Inferiority Tests of the Ratio of Treatment and Control Proportions
- Multi-Arm, Non-Inferiority Tests of the Odds Ratio of Treatment and Control Proportions
- Multi-Arm, Non-Inferiority Tests for Treatment and Control Proportions in a Cluster-Randomized Design
- Multi-Arm, Non-Inferiority Tests of the Difference Between Treatment and Control Means Assuming Equal Variance
- Multi-Arm, Non-Inferiority Tests of the Ratio of Treatment and Control Means Assuming Normal Data with Equal Variances
- Multi-Arm, Non-Inferiority Tests of the Ratio of Treatment and Control Means Assuming Log-Normal Data
- Multi-Arm, Non-Inferiority Tests of the Difference Between Treatment and Control Means Allowing Unequal Variances
- Multi-Arm, Non-Inferiority Tests for Treatment and Control Means in a Cluster-Randomized Design
- Multi-Arm, Non-Inferiority Tests Comparing Treatment and Control Survival Curves Using the Cox's Proportional Hazards Model
- Multi-Arm, Non-Inferiority Tests for Vaccine Efficacy Using the Ratio of Treatment and Control Proportions
- Multi-Arm, Non-Inferiority Tests for Vaccine Efficacy Comparing Treatment and Control Survival Curves Using the Cox's Proportional Hazards Model
- Non-Inferiority Tests for Two Means in a Cluster-Randomized Design with Clustering in Only One Arm
- Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design with Clustering in Only One Arm
- 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
- Multi-Arm Non-Inferiority Tests for Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design

## Nonparametric - 41 Scenarios

- Spearman’s Rank Correlation Tests with Simulation
- Kendall’s Tau-b Correlation Tests with Simulation
- Power Comparison of Correlation Tests with Simulation
- Tests for One Mean – (Simulation) – Wilcoxon Test
- Tests for One Mean – (Simulation) – Sign Test
- Tests for One Mean – (Simulation) – Bootstrap Test
- Tests for Paired Means (Simulation) – Wilcoxon Test
- Tests for Paired Means (Simulation) – Sign Test
- Tests for Paired Means (Simulation) – Bootstrap Test
- Mann-Whitney-Wilcoxon Tests (Simulation)
- Mann-Whitney-Wilcoxon Tests (Simulation) – Unequal n’s
- Equivalence Tests for Two Means (Simulation) – Mann-Whitney Test
- Equivalence Tests for Two Means (Simulation) – Mann-Whitney Test – Unequal n’s
- Group-Sequential Tests for Two Means (Simulation) General Assumptions – Mann-Whitney Test
- Group-Sequential Tests for Two Means (Simulation) General Assumptions – Mann-Whitney Test – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Means – Mann-Whitney Test
- Group-Sequential Non-Inferiority Tests for Two Means – Mann-Whitney Test – Unequal n’s
- Power Comparison of Tests of Means in One-Way Designs (Simulation)
- Power Comparison of Tests of Means in One-Way Designs (Simulation) – Unequal n’s
- Kruskal-Wallis Tests (Simulation)
- Kruskal-Wallis Tests (Simulation) – Unequal n’s
- Terry-Hoeffding Normal-Scores Tests of Means (Simulation)
- Terry-Hoeffding Normal-Scores Tests of Means (Simulation) – Unequal n’s
- Van der Waerden Normal Quantiles Tests of Means (Simulation)
- Van der Waerden Normal Quantiles Tests of Means (Simulation) – Unequal n’s
- Pair-wise Multiple Comparisons (Simulation) – Kruskal-Wallis
- Pair-wise Multiple Comparisons (Simulation) – Kruskal-Wallis – Unequal n’s
- Multiple Comparisons of Treatments vs. a Control (Simulation) – Kruskal-Wallis
- Multiple Comparisons of Treatments vs. a Control (Simulation) – Kruskal-Wallis – Unequal n’s
- Nonparametric Reference Intervals for Non-Normal Data
- Wilcoxon Signed-Rank Tests
- Wilcoxon Signed-Rank Tests for Non-Inferiority
- Wilcoxon Signed-Rank Tests for Superiority by a Margin
- Paired Wilcoxon Signed-Rank Tests
- Paired Wilcoxon Signed-Rank Tests for Non-Inferiority
- Paired Wilcoxon Signed-Rank Tests for Superiority by a Margin
- Mann-Whitney U or Wilcoxon Rank-Sum Tests
- Mann-Whitney U or Wilcoxon Rank-Sum Tests for Non-Inferiority
- Mann-Whitney U or Wilcoxon Rank-Sum Tests for Superiority by a Margin
- Mann-Whitney U or Wilcoxon Rank-Sum Tests (Noether)
- Stratified Wilcoxon-Mann-Whitney (van Elteren) Test

## Non-Zero and Non-Unity Null Tests - 11 Scenarios

- Non-Zero Null Tests for Simple Linear Regression
- Non-Zero Null Tests for Simple Linear Regression using R-Squared
- Non-Unity Null Tests for the Ratio of Within-Subject Variances in a Parallel Design
- Non-Unity Null Tests for the Ratio of Within-Subject Variances in a 2×2M Replicated Cross-Over Design
- Non-Zero Null Tests for the Difference of Two Within-Subject CV's in a Parallel Design
- Non-Unity Null Tests for the Ratio of Two Variances
- Non-Unity Null Tests for Two Between-Subject 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-Unity Null Tests for Two Total Variances in a 2×2 Cross-Over Design
- Non-Unity Null Tests for Two Total Variances in a Replicated Design
- Non-Unity Null Tests for Two Between Variances in a Replicated Design

## Normality Tests - 9 Scenarios

Click here to see additional details about normality test procedures in PASS.- Normality Tests (Simulation) – Anderson-Darling
- Normality Tests (Simulation) – Kolmogorov-Smirnov
- Normality Tests (Simulation) – Kurtosis
- Normality Tests (Simulation) – Martinez-Iglewicz
- Normality Tests (Simulation) – Omnibus
- Normality Tests (Simulation) – Range
- Normality Tests (Simulation) – Shapiro-Wilk
- Normality Tests (Simulation) – Skewness
- Normality Tests (Simulation) – Any Test

## Pilot Studies - 5 Scenarios

- 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
- Pilot Study Sample Size Rules of Thumb

## Proportions - One - 59 Scenarios

Click here to see additional details about one proportion procedures in PASS.- Tests for One Proportion – Exact
- Tests for One Proportion – Z-Test using S(P0)
- Tests for One Proportion – Z-Test using S(P0) with Continuity Correction
- Tests for One Proportion – Z-Test using S(Phat)
- Tests for One Proportion – Z-Test using S(Phat) with Continuity Correction
- Tests for One Proportion using Differences
- Tests for One Proportion using Ratios
- Tests for One Proportion using Odds Ratios
- Tests for One Proportion using Effect Size
- Tests for One Proportion to Demonstrate Conformance with a Reliability Standard
- Tests for One Proportion to Demonstrate Conformance with a Reliability Standard with Fixed Adverse Events
- Confidence Intervals for One Proportion – Exact (Clopper-Pearson)
- Confidence Intervals for One Proportion – Score (Wilson)
- Confidence Intervals for One Proportion – Score with Continuity Correction
- Confidence Intervals for One Proportion – Simple Asymptotic
- Confidence Intervals for One Proportion – Simple Asymptotic with Continuity Correction
- 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 Tests for One Proportion – Exact
- Non-Inferiority Tests for One Proportion – Z-Test using S(P0)
- Non-Inferiority Tests for One Proportion – Z-Test using S(P0) with Continuity Correction
- Non-Inferiority Tests for One Proportion – Z-Test using S(Phat)
- Non-Inferiority Tests for One Proportion – Z-Test using S(Phat) with Continuity Correction
- Non-Inferiority Tests for One Proportion using Differences
- Non-Inferiority Tests for One Proportion using Ratios
- Non-Inferiority Tests for One Proportion using Odds Ratios
- Equivalence Tests for One Proportion – Exact Test
- Equivalence Tests for One Proportion – Z Test using S(P0)
- Equivalence Tests for One Proportion – Z Test using S(P0) with Continuity Correction
- Equivalence Tests for One Proportion – Z Test using S(Phat)
- Equivalence Tests for One Proportion – Z Test using S(Phat) with Continuity Correction
- Equivalence Tests for One Proportion using Differences
- Equivalence Tests for One Proportion using Ratios
- Equivalence Tests for One Proportion using Odds Ratios
- Superiority by a Margin Tests for One Proportion – Exact
- Superiority by a Margin Tests for One Proportion – Z-Test using S(P0)
- Superiority by a Margin Tests for One Proportion – Z-Test using S(P0) with Continuity Correction
- Superiority by a Margin Tests for One Proportion – Z-Test using S(Phat)
- Superiority by a Margin Tests for One Proportion – Z-Test using S(Phat) with Continuity Correction
- Superiority by a Margin Tests for One Proportion using Differences
- Superiority by a Margin Tests for One Proportion using Ratios
- Superiority by a Margin Tests for One Proportion using Odds Ratios
- Single-Stage Phase II Clinical Trials
- Two-Stage Phase II Clinical Trials
- Three-Stage Phase II Clinical Trials
- Post-Marketing Surveillance – Cohort – No Background Incidence
- Post-Marketing Surveillance – Cohort – Known Background Incidence
- Post-Marketing Surveillance – Cohort – Unknown Background Incidence
- Post-Marketing Surveillance – Matched Case-Control Study
- Conditional Power of One Proportion Tests
- 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
- Group-Sequential Tests for One Proportion in a Fleming Design
- Conditional Power of Non-Inferiority Tests for One Proportion
- Conditional Power of Superiority by a Margin Tests for One Proportion
- Two-Stage Designs for Tests of One Proportion (Simon)

## Proportions - Two Independent - 208 Scenarios

Click here to see additional details about two proportions procedures in PASS.- Tests for Two Proportions – Fisher’s Exact Test
- Tests for Two Proportions – Fisher’s Exact Test – Unequal n’s
- Tests for Two Proportions – Z-Test (Pooled)
- Tests for Two Proportions – Z-Test (Pooled) – Unequal n’s
- Tests for Two Proportions – Z-Test (Unpooled)
- Tests for Two Proportions – Z-Test (Unpooled) – Unequal n’s
- Tests for Two Proportions – Z-Test (Pooled) with Continuity Correction
- Tests for Two Proportions – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Tests for Two Proportions – Z-Test (Unpooled) with Continuity Correction
- Tests for Two Proportions – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Tests for Two Proportions – Mantel-Haenszel Test
- Tests for Two Proportions – Mantel-Haenszel Test – Unequal n’s
- Tests for Two Proportions – Likelihood Ratio Test
- Tests for Two Proportions – Likelihood Ratio Test – Unequal n’s
- Tests for Two Proportions using Differences
- Tests for Two Proportions using Ratios
- Tests for Two Proportions using Odds Ratios
- Tests for Two Proportions using Effect Size
- Tests for Two Proportions using Effect Size – Unequal n’s
- Confidence Intervals for Two Proportions – Score (Farrington & Manning)
- Confidence Intervals for Two Proportions – Score (Farrington & Manning) – Unequal n’s
- Confidence Intervals for Two Proportions – Score (Miettinen & Nurminen)
- Confidence Intervals for Two Proportions – Score (Miettinen & Nurminen) – Unequal n’s
- Confidence Intervals for Two Proportions – Score with Skewness (Gart & Nam)
- Confidence Intervals for Two Proportions – Score with Skewness (Gart & Nam) – Unequal n’s
- Confidence Intervals for Two Proportions – Score (Wilson)
- Confidence Intervals for Two Proportions – Score (Wilson) – Unequal n’s
- Confidence Intervals for Two Proportions – Score with Continuity Correction (Wilson)
- Confidence Intervals for Two Proportions – Score with Continuity Correction (Wilson) – Unequal n’s
- Confidence Intervals for Two Proportions – Chi-Square with Continuity Correction (Yates)
- Confidence Intervals for Two Proportions – Chi-Square with Continuity Correction (Yates) – Unequal n’s
- Confidence Intervals for Two Proportions – Chi-Square (Pearson)
- Confidence Intervals for Two Proportions – Chi-Square (Pearson) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Score (Farrington & Manning)
- Confidence Intervals for Two Proportions using Ratios – Score (Farrington & Manning) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Score (Miettinen & Nurminen)
- Confidence Intervals for Two Proportions using Ratios – Score (Miettinen & Nurminen) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Score with Skewness (Gart & Nam)
- Confidence Intervals for Two Proportions using Ratios – Score with Skewness (Gart & Nam) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Logarithm (Katz)
- Confidence Intervals for Two Proportions using Ratios – Logarithm (Katz) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Logarithm + ½ (Walter)
- Confidence Intervals for Two Proportions using Ratios – Logarithm + ½ (Walter) – Unequal n’s
- Confidence Intervals for Two Proportions using Ratios – Fleiss
- Confidence Intervals for Two Proportions using Ratios – Fleiss – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Exact (Conditional)
- Confidence Intervals for Two Proportions using Odds Ratios – Exact (Conditional) – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Score (Farrington & Manning)
- Confidence Intervals for Two Proportions using Odds Ratios – Score (Farrington & Manning) – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Score (Miettinen & Nurminen)
- Confidence Intervals for Two Proportions using Odds Ratios – Score (Miettinen & Nurminen) – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Fleiss
- Confidence Intervals for Two Proportions using Odds Ratios – Fleiss – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Logarithm
- Confidence Intervals for Two Proportions using Odds Ratios – Logarithm – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Mantel-Haenszel
- Confidence Intervals for Two Proportions using Odds Ratios – Mantel-Haenszel – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Simple
- Confidence Intervals for Two Proportions using Odds Ratios – Simple – Unequal n’s
- Confidence Intervals for Two Proportions using Odds Ratios – Simple + 1/2
- Confidence Intervals for Two Proportions using Odds Ratios – Simple + 1/2 – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Z-Test (Pooled)
- Non-Inferiority Tests for Two Proportions – Z-Test (Pooled) – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Z-Test (Unpooled)
- Non-Inferiority Tests for Two Proportions – Z-Test (Unpooled) – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Z-Test (Pooled) with Continuity Correction
- Non-Inferiority Tests for Two Proportions – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Z-Test (Unpooled) with Continuity Correction
- Non-Inferiority Tests for Two Proportions – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Farrington & Manning)
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Farrington & Manning) – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen)
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Gart & Nam)
- Non-Inferiority Tests for Two Proportions – Likelihood Score (Gart & Nam) – Unequal n’s
- Non-Inferiority Tests for Two Proportions using Differences
- Non-Inferiority Tests for Two Proportions using Ratios
- Non-Inferiority Tests for Two Proportions using Odds Ratios
- Equivalence Tests for Two Proportions – Z Test (Pooled)
- Equivalence Tests for Two Proportions – Z Test (Pooled) – Unequal n’s
- Equivalence Tests for Two Proportions – Z Test (Unpooled)
- Equivalence Tests for Two Proportions – Z Test (Unpooled) – Unequal n’s
- Equivalence Tests for Two Proportions – Z Test (Pooled) with Continuity Correction
- Equivalence Tests for Two Proportions – Z Test (Pooled) with Continuity Correction – Unequal n’s
- Equivalence Tests for Two Proportions – Z Test (Unpooled) with Continuity Correction
- Equivalence Tests for Two Proportions – Z Test (Unpooled) with Continuity Correction – Unequal n’s
- Equivalence Tests for Two Proportions – Likelihood Score (Farrington & Manning)
- Equivalence Tests for Two Proportions – Likelihood Score (Farrington & Manning) – Unequal n’s
- Equivalence Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen)
- Equivalence Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Equivalence Tests for Two Proportions – Likelihood Score (Gart & Nam)
- Equivalence Tests for Two Proportions – Likelihood Score (Gart & Nam) – Unequal n’s
- Equivalence Tests for Two Proportions using Differences
- Equivalence Tests for Two Proportions using Ratios
- Equivalence Tests for Two Proportions using Odds Ratios
- Superiority by a Margin Tests for Two Proportions – Z-Test (Pooled)
- Superiority by a Margin Tests for Two Proportions – Z-Test (Pooled) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Z-Test (Unpooled)
- Superiority by a Margin Tests for Two Proportions – Z-Test (Unpooled) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Z-Test (Pooled) with Continuity Correction
- Superiority by a Margin Tests for Two Proportions – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Z-Test (Unpooled) with Continuity Correction
- Superiority by a Margin Tests for Two Proportions – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Farrington & Manning)
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Farrington & Manning) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen)
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Gart & Nam)
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Gart & Nam) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions using Differences
- Superiority by a Margin Tests for Two Proportions using Ratios
- Superiority by a Margin Tests for Two Proportions using Odds Ratios
- Tests for Two Proportions in a Repeated Measures Design using Odds Ratios – Difference
- Tests for Two Proportions in a Repeated Measures Design using Odds Ratios – Difference – Unequal n’s
- Tests for Two Proportions in a Repeated Measures Design using Odds Ratios – Log(OR)
- Tests for Two Proportions in a Repeated Measures Design using Odds Ratios – Log(OR) – Unequal n’s
- Tests for Two Proportions in a Repeated Measures Design using Proportions
- Group-Sequential Tests for Two Proportions
- Group-Sequential Tests for Two Proportions – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Pooled)
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Pooled) – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Unpooled)
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Unpooled) – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction
- Group-Sequential Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Mantel-Haenszel
- Group-Sequential Tests for Two Proportions (Simulation) – Mantel-Haenszel – Unequal n’s
- Group-Sequential Tests for Two Proportions (Simulation) – Fisher’s Exact
- Group-Sequential Tests for Two Proportions (Simulation) – Fisher’s Exact – Unequal n’s
- Group-Sequential Tests for Two Proportions using Differences (Simulation)
- Group-Sequential Tests for Two Proportions using Ratios (Simulation)
- Group-Sequential Tests for Two Proportions using Odds Ratios (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Pooled)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Pooled) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Unpooled)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Unpooled) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Gart & Nam)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Likelihood Score (Gart & Nam) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Proportions using Differences (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions using Ratios (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions using Odds Ratios (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Gart & Nam)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Gart & Nam) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions using Differences (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Proportions using Ratios (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Proportions using Odds Ratios (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Proportions (Simulation) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Unequal n’s
- Conditional Power of Two-Proportions Tests
- Conditional Power of Two-Proportions Tests – Unequal n’s
- Tests for Two Proportions in a Stratified Design (Cochran/Mantel-Haenzel Test)
- Tests for Two Proportions in a Stratified Design (Cochran/Mantel-Haenzel Test) – Unequal n’s
- Tests for Two Proportions in a Repeated Measures Design
- Tests for Two Proportions in a Repeated Measures Design – Unequal n’s
- Tests for Two Proportions in a Repeated Measures Design using Odds Ratios
- Tests for Two Proportions in a Stepped-Wedge Cluster-Randomized Design - Complete Design
- Tests for Two Proportions in a Stepped-Wedge Cluster-Randomized Design - Incomplete Design (Custom)
- 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)
- Group-Sequential Tests for Two Proportions (Simulation)
- Conditional Power of Non-Inferiority Tests for the Difference Between Two Proportions
- Conditional Power of Superiority by a Margin Tests for the Difference Between Two 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
- 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
- Tests for Two Proportions in a Split-Mouth Design
- Tests for Two Proportions in a Stratified Cluster-Randomized Design (Cochran-Mantel-Haenszel Test)
- 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
- Tests for Two Proportions in a Cluster-Randomized Design with Clustering in Only One Arm
- Non-Inferiority Tests for Two Proportions in a Cluster-Randomized Design with Clustering in Only One Arm

## Proportions - Correlated or Paired - 14 Scenarios

Click here to see additional details about correlated proportions procedures in PASS.- Tests for Two Correlated Proportions (McNemar's Test)
- Tests for Two Correlated Proportions (McNemar's Test) using Odds Ratios
- Tests for Two Correlated Proportions in a Matched Case-Control Design
- Tests for the Odds Ratio in a Matched Case-Control Design with a Binary Covariate using Conditional Logistic Regression
- Tests for the Odds Ratio in a Matched Case-Control Design with a Quantitative X using Conditional Logistic Regression
- Tests for the Matched-Pair Difference of Two Proportions in a Cluster-Randomized Design
- Non-Inferiority Tests for Two Correlated Proportions
- Non-Inferiority Tests for Two Correlated Proportions using Ratios
- Equivalence Tests for Two Correlated Proportions
- Equivalence Tests for Two Correlated Proportions using Ratios
- 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 Correlated Proportions with Dropout
- Tests for Two Correlated Proportions with Incomplete Observations

## Proportions - Cross-Over Designs - 12 Scenarios

- Tests for the Odds Ratio 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
- Superiority by a Margin Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
- Equivalence Tests for the Odds Ratio of Two Proportions in a 2x2 Cross-Over Design
- Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
- Non-Inferiority Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
- Superiority by a Margin Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
- Equivalence Tests for the Difference of Two Proportions in a 2x2 Cross-Over Design
- Tests for Pairwise Proportion Differences in a Williams Cross-Over Design
- Non-Inferiority Tests for Pairwise Proportion Differences in a Williams Cross-Over Design
- Superiority by a Margin Tests for Pairwise Proportion Differences in a Williams Cross-Over Design
- Equivalence Tests for Pairwise Proportion Differences in a Williams Cross-Over Design

## Proportions - Many - 34 Scenarios

Click here to see additional details about chi-square and other proportions tests procedures in PASS.- Chi-Square Contingency Table Test
- Chi-Square Multinomial Test
- Cochran-Armitage Test for Trend in Proportions
- Cochran-Armitage Test for Trend in Proportions – Unequal n’s
- Multiple Comparisons of Proportions vs. Control
- Multiple Comparisons of Proportions vs. Control – Unequal n’s
- Logistic Regression
- Tests for Two Ordered Categorical Variables
- Tests for Two Ordered Categorical Variables – Unequal n’s
- GEE Tests for the TAD of Multiple Groups in a Repeated Measures Design (Binary Outcome)
- Tests for Multiple Correlated Proportions
- GEE Tests for Multiple Proportions in a Cluster-Randomized Design
- Tests for Multiple Proportions in a One-Way Design
- Multi-Arm Tests for Treatment and Control Proportions
- Multi-Arm, Non-Inferiority Tests of the Difference Between Treatment and Control Proportions
- Multi-Arm, Superiority by a Margin Tests of the Difference Between Treatment and Control Proportions
- Multi-Arm, Equivalence Tests of the Difference Between Treatment and Control Proportions
- Multi-Arm, Non-Inferiority Tests of the Ratio of Treatment and Control Proportions
- Multi-Arm, Superiority by a Margin Tests of the Ratio of Treatment and Control Proportions
- Multi-Arm, Equivalence Tests of the Ratio of Treatment and Control Proportions
- Multi-Arm, Non-Inferiority Tests of the Odds Ratio of Treatment and Control Proportions
- Multi-Arm, Superiority by a Margin Tests of the Odds Ratio of Treatment and Control Proportions
- Multi-Arm, Equivalence Tests of the Odds Ratio of Treatment and Control Proportions
- Multi-Arm Tests for Treatment and Control Proportions in a Cluster-Randomized Design
- Multi-Arm, Non-Inferiority Tests for 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
- 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 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 the Ratio 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 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

## Quality Control - 16 Scenarios

- Acceptance Sampling for Attributes
- Operating Characteristic Curves for Acceptance Sampling for Attributes
- Acceptance Sampling for Attributes with Zero Nonconformities
- Acceptance Sampling for Attributes with Fixed Nonconformities
- Quality Control Charts for Means – Shewhart (Xbar) (Simulation)
- Quality Control Charts for Means – CUSUM (Simulation)
- Quality Control Charts for Means – CUSUM + Shewhart (Simulation)
- Quality Control Charts for Means – FIR CUSUM (Simulation)
- Quality Control Charts for Means – FIR CUSUM + Shewhart (Simulation)
- Quality Control Charts for Means – EWMA (Simulation)
- Quality Control Charts for Means – EWMA + Shewhart (Simulation)
- Quality Control Charts for Variability – R (Simulation)
- Quality Control Charts for Variability – S (Simulation)
- Quality Control Charts for Variability – S with Probability Limits (Simulation)
- Confidence Intervals for Cp
- Confidence Intervals for Cpk

## Rates and Counts - 37 Scenarios

- Tests for the Difference Between Two Poisson Rates
- Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design
- Tests for the Matched-Pair Difference of Two Event Rates in a Cluster-Randomized Design
- Tests for the Ratio of Two Poisson Rates (Zhu)
- Tests for the Ratio of Two Negative Binomial Rates
- Poisson Means (Incidence Rates)
- Post-Marketing Surveillance (Incidence Rates)
- Tests for Two Poisson Rates in a Stepped-Wedge Cluster-Randomized Design - Complete Design
- Tests for Two Poisson Rates in a Stepped-Wedge Cluster-Randomized Design - Incomplete Design (Custom)
- Poisson Regression
- Equivalence Tests for the Ratio of Two Poisson Rates
- Equivalence Tests for the Ratio of Two Poisson Rates – Unequal n’s
- Equivalence Tests for the Ratio of Two Negative Binomial Rates
- Equivalence Tests for the Ratio of Two Negative Binomial Rates – Unequal n’s
- Non-Inferiority Tests for the Ratio of Two Poisson Rates
- Non-Inferiority Tests for the Ratio of Two Poisson Rates – Unequal n’s
- Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates
- Non-Inferiority Tests for the Ratio of Two Negative Binomial Rates – Unequal n’s
- Superiority by a Margin Tests for the Ratio of Two Poisson Rates
- Superiority by a Margin Tests for the Ratio of Two Poisson Rates – Unequal n’s
- Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
- Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates – Unequal n’s
- GEE Tests for the Slope of Two Groups in a Repeated Measures Design (Count Outcome)
- GEE 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)
- 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
- Tests of Mediation Effect in Poisson Regression
- GEE Tests for Multiple Poisson Rates in a Cluster-Randomized Design
- 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)
- Tests for the Difference Between Two Poisson Rates in a Cluster-Randomized Design with Adjustment for Varying Cluster Sizes
- Tests for Multiple Poisson Rates in a One-Way Design

## Reference Intervals - 2 Scenarios

- Reference Intervals for Normal Data
- Nonparametric Reference Intervals for Non-Normal Data

## Regression - 42 Scenarios

Click here to see additional details about regression procedures in PASS.- Linear Regression
- Confidence Intervals for Linear Regression Slope
- Tests for the Difference Between Two Linear Regression Slopes
- Tests for the Difference Between Two Linear Regression Intercepts
- Cox Regression
- Logistic Regression
- Logistic Regression with One Binary Covariate using the Wald Test
- Logistic Regression with Two Binary Covariates using the Wald Test
- Logistic Regression with Two Binary Covariates and an Interaction using the Wald Test
- Confidence Intervals for the Odds Ratio in a Logistic Regression with Two Binary Covariates
- Confidence Intervals for the Interaction Odds Ratio in a Logistic Regression with Two Binary Covariates
- Tests for the Odds Ratio in a Matched Case-Control Design with a Binary X using Conditional Logistic Regression
- Tests for the Odds Ratio in a Matched Case-Control Design with a Quantitative X using Conditional Logistic Regression
- Multiple Regression
- Multiple Regression using Effect Size
- Poisson Regression
- Probit Analysis - Probit
- Probit Analysis – Logit
- Confidence Intervals for Michaelis-Menten Parameters
- Confidence Intervals for Michaelis-Menten Parameters – Unequal n’s
- Reference Intervals for Clinical and Lab Medicine
- Mendelian Randomization with a Binary Outcome
- Mendelian Randomization with a Continuous Outcome
- Tests for the Odds Ratio in a Matched Case-Control Design with a Binary Covariate using Conditional Logistic Regression
- Tests for the Odds Ratio in a Matched Case-Control Design with a Quantitative X using Conditional Logistic Regression
- 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 Xs (Wald Test)
- Tests for the Odds Ratio in Logistic Regression with One Binary X and Other Xs (Wald Test)
- Tests of Mediation Effect using the Sobel Test
- Tests of Mediation Effect in Linear Regression
- Tests of Mediation Effect in Logistic Regression
- Tests of Mediation Effect in Poisson Regression
- Tests of Mediation Effect in Cox Regression
- Joint Tests of Mediation in Linear Regression with Continuous Variables
- Simple Linear Regression
- Non-Zero Null Tests for Simple Linear Regression
- Non-Inferiority Tests for Simple Linear Regression
- Superiority by a Margin Tests for Simple Linear Regression
- Equivalence Tests for Simple Linear Regression
- Simple Linear Regression using R-Squared
- Non-Zero Null Tests for Simple Linear Regression using R-Squared
- Deming Regression

## ROC Curves - 10 Scenarios

- Tests for One ROC Curve – Discrete Data
- Tests for One ROC Curve – Continuous Data
- Tests for One ROC Curve – Continuous Data – Unequal n’s
- Tests for Two ROC Curves – Discrete Data
- Tests for Two ROC Curves – Discrete Data – Unequal n’s
- Tests for Two ROC Curves – Continuous Data
- Tests for Two ROC Curves – Continuous Data – Unequal n’s
- Confidence Intervals for the Area Under an ROC Curve
- Confidence Intervals for the Area Under an ROC Curve – Unequal n’s

## Sensitivity and Specificity - 21 Scenarios

- Tests for One-Sample Sensitivity and Specificity
- Tests for Paired Sensitivities
- Tests for Two Independent Sensitivities – Fisher’s Exact Test
- Tests for Two Independent Sensitivities – Fisher’s Exact Test – Unequal n’s
- Tests for Two Independent Sensitivities – Z-Test (Pooled)
- Tests for Two Independent Sensitivities – Z-Test (Pooled) – Unequal n’s
- Tests for Two Independent Sensitivities – Z-Test (Unpooled)
- Tests for Two Independent Sensitivities – Z-Test (Unpooled) – Unequal n’s
- Tests for Two Independent Sensitivities – Z-Test (Pooled) with Continuity Correction
- Tests for Two Independent Sensitivities – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Tests for Two Independent Sensitivities – Z-Test (Unpooled) with Continuity Correction
- Tests for Two Independent Sensitivities – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Tests for Two Independent Sensitivities – Mantel-Haenszel Test
- Tests for Two Independent Sensitivities – Mantel-Haenszel Test – Unequal n’s
- Tests for Two Independent Sensitivities – Likelihood Ratio Test
- Tests for Two Independent Sensitivities – Likelihood Ratio Test – Unequal n’s
- Confidence Intervals for One-Sample Sensitivity
- Confidence Intervals for One-Sample Specificity
- Confidence Intervals for One-Sample Sensitivity and Specificity
- Tests for Paired Specificities
- Tests for Two Independent Specificities

## Single-Case (AB)K Designs - 1 Scenario

- Tests for the Difference Between Treatment and Control Means in Single-Case (AB)K Designs

## Superiority by a Margin Tests - 136 Scenarios

- Superiority by a Margin Tests for One Mean
- Superiority by a Margin Tests for Paired Means
- Superiority by a Margin Tests for Two Means using Differences
- Superiority by a Margin Tests for Two Means using Differences – Unequal n’s
- Superiority by a Margin Tests for Two Means using Ratios
- Superiority by a Margin Tests for Two Means using Ratios – Unequal n’s
- Superiority by a Margin Tests for the Ratio of Two Poisson Rates
- Superiority by a Margin Tests for the Ratio of Two Poisson Rates – Unequal n’s
- Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates
- Superiority by a Margin Tests for the Ratio of Two Negative Binomial Rates – Unequal n’s
- Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design using Differences
- Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design using Ratios
- Superiority by a Margin Tests for Two Means in a Higher-Order Cross-Over Design using Differences
- Superiority by a Margin Tests for Two Means in a Higher-Order Cross-Over Design using Ratios
- Superiority by a Margin Tests for Two Means in a Cluster-Randomized Design
- Superiority by a Margin Tests for One Proportion – Exact
- Superiority by a Margin Tests for One Proportion – Z-Test using S(P0)
- Superiority by a Margin Tests for One Proportion – Z-Test using S(P0) with Continuity Correction
- Superiority by a Margin Tests for One Proportion – Z-Test using S(Phat)
- Superiority by a Margin Tests for One Proportion – Z-Test using S(Phat) with Continuity Correction
- Superiority by a Margin Tests for One Proportion using Differences
- Superiority by a Margin Tests for One Proportion using Ratios
- Superiority by a Margin Tests for One Proportion using Odds Ratios
- Superiority by a Margin Tests for Two Proportions – Z-Test (Pooled)
- Superiority by a Margin Tests for Two Proportions – Z-Test (Pooled) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Z-Test (Unpooled)
- Superiority by a Margin Tests for Two Proportions – Z-Test (Unpooled) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Z-Test (Pooled) with Continuity Correction
- Superiority by a Margin Tests for Two Proportions – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Z-Test (Unpooled) with Continuity Correction
- Superiority by a Margin Tests for Two Proportions – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Farrington & Manning)
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Farrington & Manning) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen)
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Gart & Nam)
- Superiority by a Margin Tests for Two Proportions – Likelihood Score (Gart & Nam) – Unequal n’s
- Superiority Test of Two Proportions from a Cluster-Randomized Design – Z Test (Pooled)
- Superiority Test of Two Proportions from a Cluster-Randomized Design – Z Test (Pooled) – Unequal n’s
- Superiority Test of Two Proportions from a Cluster-Randomized Design – Z Test (Unpooled)
- Superiority Test of Two Proportions from a Cluster-Randomized Design – Z Test (Unpooled) – Unequal n’s
- Superiority Test of Two Proportions from a Cluster-Randomized Design – Likelihood Score Test
- Superiority Test of Two Proportions from a Cluster-Randomized Design – Likelihood Score Test – Unequal n’s
- Superiority by a Margin Tests for Two Proportions using Differences
- Superiority by a Margin Tests for Two Proportions using Ratios
- Superiority by a Margin Tests for Two Proportions using Odds Ratios
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Pooled) with Continuity Correction – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Z-Test (Unpooled) with Continuity Correction – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Farrington & Manning) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Miettinen & Nurminen) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Gart & Nam)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Likelihood Score (Gart & Nam) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions using Differences (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Proportions using Ratios (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Proportions using Odds Ratios (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Hazard Rates (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Hazard Rates (Simulation) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Means with Known Variances (Simulation) – Unequal n’s
- Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation)
- Group-Sequential Superiority by a Margin T-Tests for Two Means (Simulation) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Proportions (Simulation) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design – Z Test (Pooled)
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design – Z Test (Pooled) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design – Z Test (Unpooled)
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design – Z Test (Unpooled) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design – Z Test (Pooled)
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design – Z Test (Pooled) – Unequal n’s
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design using Proportions
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design using Differences
- Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design using Ratios
- 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 – Unequal n’s
- Superiority by a Margin Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
- Superiority by a Margin Tests for the Difference of Two Hazard Rates Assuming an Exponential Model – Unequal n’s
- 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 Difference of Two Proportions in a 2x2 Cross-Over Design
- 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 Gen. Odds Ratio for Ordinal Data in a 2x2 Cross-Over Design
- Superiority by a Margin Tests for Pairwise Proportion Differences in a Williams Cross-Over Design
- Superiority by a Margin Tests for Pairwise Mean Differences in a Williams Cross-Over Design
- Conditional Power of Two-Sample T-Tests for Superiority by a Margin
- Conditional Power of Superiority by a Margin Tests for the Difference Between Two Proportions
- Conditional Power of Superiority by a Margin Logrank Tests
- Conditional Power of Superiority by a Margin Tests for Two Means in a 2x2 Cross-Over Design
- Conditional Power of One-Sample T-Tests for Superiority by a Margin
- Conditional Power of Paired T-Tests for Superiority by a Margin
- Conditional Power of Superiority by a Margin Tests for One Proportion
- 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
- 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 Simple Linear Regression
- 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 the Ratio of Two Variances
- 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 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 Between Variances in a Replicated Design
- One-Sample Z-Tests for Superiority by a Margin
- Wilcoxon Signed-Rank Tests for Superiority by a Margin
- Paired T-Tests for Superiority by a Margin
- Paired Z-Tests for Superiority by a Margin
- Paired Wilcoxon Signed-Rank Tests for 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
- Multi-Arm, Superiority by a Margin Tests of the Difference Between Treatment and Control Proportions
- Multi-Arm, Superiority by a Margin Tests of the Ratio of Treatment and Control Proportions
- Multi-Arm, Superiority by a Margin Tests of the Odds Ratio of Treatment and Control Proportions
- Multi-Arm, Superiority by a Margin Tests of the Difference Between Treatment and Control Means Assuming Equal Variance
- Multi-Arm, Superiority by a Margin Tests of the Ratio of Treatment and Control Means Assuming Normal Data with Equal Variance
- Multi-Arm, Superiority by a Margin Tests of the Ratio of Treatment and Control Means Assuming Log-Normal Data
- Multi-Arm, Superiority by a Margin Tests of the Difference Between Treatment and Control Means Allowing Unequal Variances
- Multi-Arm, Superiority by a Margin Tests Comparing Treatment and Control Survival Curves Using the Cox's Proportional Hazards Model
- 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 Comparing Treatment and Control Survival Curves Using the Cox's Proportional Hazards Model
- 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 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 Superiority by a Margin 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 Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design

## Survival Analysis - 97 Scenarios

Click here to see additional details about survival procedures in PASS.- One-Sample Logrank Tests
- One-Sample Cure Model Tests
- Logrank Tests (Input Hazard Rates)
- Logrank Tests (Input Median Survival Times)
- Logrank Tests (Input Proportion Surviving)
- Logrank Tests (Input Mortality)
- Logrank Tests for Two Survival Curves Using Cox’s Proportional Hazards Model
- Logrank Tests – Unequal n’s
- Two-Group Survival Comparison Tests (Simulation) – Logrank
- Two-Group Survival Comparison Tests (Simulation) – Logrank – Unequal n’s
- Two-Group Survival Comparison Tests (Simulation) – Gehan-Wilcoxon
- Two-Group Survival Comparison Tests (Simulation) – Gehan-Wilcoxon – Unequal n’s
- Two-Group Survival Comparison Tests (Simulation) – Tarone-Ware
- Two-Group Survival Comparison Tests (Simulation) – Tarone-Ware – Unequal n’s
- Two-Group Survival Comparison Tests (Simulation) – Peto-Peto
- Two-Group Survival Comparison Tests (Simulation) – Peto-Peto – Unequal n’s
- Two-Group Survival Comparison Tests (Simulation) – Modified Peto-Peto
- Two-Group Survival Comparison Tests (Simulation) – Modified Peto-Peto – Unequal n’s
- Two-Group Survival Comparison Tests (Simulation) – Fleming-Harrington Custom Parameters
- Two-Group Survival Comparison Tests (Simulation) – Fleming-Harrington Custom Parameters – Unequal n’s
- Logrank Tests in a Cluster-Randomized Design
- Tests for Two Survival Curves using Cox’s Proportional Hazards Model
- Tests for Two Survival Curves using Cox’s Proportional Hazards Model – Unequal n’s
- Tests for the Difference of Two Hazard Rates Assuming an Exponential Model
- Tests for the Difference of Two Hazard Rates Assuming an Exponential Model – Unequal n’s
- Logrank Tests Accounting for Competing Risks
- Logrank Tests Accounting for Competing Risks – Unequal n’s
- Non-Inferiority Logrank Tests
- Non-Inferiority Logrank Tests – Unequal n’s
- 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 – Unequal n’s
- Non-Inferiority Tests for Difference of Two Hazard Rates Assuming an Exponential Model
- Non-Inferiority Tests for Difference of Two Hazard Rates Assuming an Exponential Model – Unequal n’s
- Equivalence Tests for Two Survival Curves using Cox’s Proportional Hazards Model
- Equivalence Tests for Two Survival Curves using Cox’s Proportional Hazards Model – Unequal n’s
- Equivalence Tests for Difference of Two Hazard Rates Assuming an Exponential Model
- Equivalence Tests for Difference of Two Hazard Rates Assuming an Exponential Model – Unequal n’s
- 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 – Unequal n’s
- Superiority by a Margin Tests for Difference of Two Hazard Rates Assuming an Exponential Model
- Superiority by a Margin Tests for Difference of Two Hazard Rates Assuming an Exponential Model – Unequal n’s
- Group-Sequential Logrank Tests of Two Survival Curves assuming Exponential Survival
- Group-Sequential Logrank Tests of Two Survival Curves assuming Proportional Hazards
- Group-Sequential Logrank Tests using Hazard Rates (Simulation)
- Group-Sequential Logrank Tests using Median Survival Times (Simulation)
- Group-Sequential Logrank Tests using Proportion Surviving (Simulation)
- Group-Sequential Logrank Tests using Mortality (Simulation)
- Group-Sequential Logrank Tests (Simulation) – Unequal n’s
- Group-Sequential Logrank Tests (Simulation) – Gehan-Wilcoxon
- Group-Sequential Logrank Tests (Simulation) – Gehan-Wilcoxon – Unequal n’s
- Group-Sequential Logrank Tests (Simulation) – Tarone-Ware
- Group-Sequential Logrank Tests (Simulation) – Tarone-Ware – Unequal n’s
- Group-Sequential Logrank Tests (Simulation) – Peto-Peto
- Group-Sequential Logrank Tests (Simulation) – Peto-Peto – Unequal n’s
- Group-Sequential Logrank Tests (Simulation) – Modified Peto-Peto
- Group-Sequential Logrank Tests (Simulation) – Modified Peto-Peto – Unequal n’s
- Group-Sequential Logrank Tests (Simulation) – Fleming-Harrington Custom Parameters
- Group-Sequential Logrank Tests (Simulation) – Fleming-Harrington Custom Parameters – Unequal n’s
- Group-Sequential Tests for Two Hazard Rates (Simulation)
- Group-Sequential Tests for Two Hazard Rates (Simulation) – Unequal n’s
- Group-Sequential Non-Inferiority Tests for Two Hazard Rates (Simulation)
- Group-Sequential Non-Inferiority Tests for Two Hazard Rates (Simulation) – Unequal n’s
- Group-Sequential Superiority by a Margin Tests for Two Hazard Rates (Simulation)
- Group-Sequential Superiority by a Margin Tests for Two Hazard Rates (Simulation) – Unequal n’s
- Conditional Power of Logrank Tests
- Cox Regression
- Tests for One Exponential Mean with Replacement
- Tests for One Exponential Mean without Replacement
- Tests for Two Exponential Means
- Tests for Two Exponential Means – Unequal n’s
- Confidence Intervals for the Exponential Lifetime Mean
- Confidence Intervals for the Exponential Hazard Rate
- Confidence Intervals for an Exponential Lifetime Percentile
- Confidence Intervals for Exponential Reliability
- Probit Analysis - Probit
- Probit Analysis – Logit
- Logrank Tests – Freedman
- Logrank Tests – Freedman – Unequal n’s
- Logrank Tests – Lachin and Foulkes
- Logrank Tests – Lachin and Foulkes – Unequal n’s
- Conditional Power of Non-Inferiority Logrank Tests
- Conditional Power of Superiority by a Margin Logrank Tests
- Tests of Mediation Effect in Cox Regression
- One-Sample Tests for Exponential Hazard Rate
- Multi-Arm Tests Comparing Treatment and Control Survival Curves Using the Cox's Proportional Hazards Model
- Multi-Arm, Non-Inferiority Tests Comparing Treatment and Control Survival Curves Using the Cox's Proportional Hazards Model
- Multi-Arm, Superiority by a Margin Tests Comparing Treatment and Control Survival Curves Using the Cox's Proportional Hazards Model
- Multi-Arm, Equivalence Tests Comparing Treatment and Control Survival Curves Using the Cox's Proportional Hazards Model
- Multi-Arm, Non-Inferiority Tests for Vaccine Efficacy Comparing Treatment and Control Survival Curves Using the Cox's Proportional Hazards Model
- Multi-Arm, Superiority by a Margin Tests for Vaccine Efficacy Comparing Treatment and Control Survival Curves Using the Cox's Proportional Hazards Model
- Multi-Arm Tests for Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Multi-Arm Non-Inferiority Tests for Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Multi-Arm Superiority by a Margin Tests for Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Multi-Arm Equivalence Tests for Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Tests for Two Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Non-Inferiority Tests for Two Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Superiority by a Margin Tests for Two Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design
- Equivalence Tests for Two Survival Curves using Cox's Proportional Hazards in a Cluster-Randomized Design

## Tolerance Intervals - 6 Scenarios

- Tolerance Intervals for Normal Data
- Tolerance Intervals for Any Data (Nonparametric)
- Tolerance Intervals for Exponential Data
- Tolerance Intervals for Gamma Data
- Tests for One Proportion to Demonstrate Conformance with a Reliability Standard
- Tests for One Proportion to Demonstrate Conformance with a Reliability Standard with Fixed Adverse Events

## Two-Part Models - 2 Scenarios

- Tests for Two Groups Assuming a Two-Part Model
- Tests for Two Groups Assuming a Two-Part Model with Detection Limits

## Variances and Standard Deviations - 68 Scenarios

Click here to see additional details about variances and standard deviations in PASS.- Tests for One Variance
- Tests for Two Variances
- Tests for Two Variances – Unequal n’s
- Bartlett Test of Variances (Simulation)
- Bartlett Test of Variances (Simulation) – Unequal n’s
- Levene Test of Variances (Simulation)
- Levene Test of Variances (Simulation) – Unequal n’s
- Brown-Forsythe Test of Variances (Simulation)
- Brown-Forsythe Test of Variances (Simulation) – Unequal n’s
- Conover Test of Variances (Simulation)
- Conover Test of Variances (Simulation) – Unequal n’s
- Power Comparison of Tests of Variances with Simulation
- Power Comparison of Tests of Variances with Simulation – Unequal n’s
- 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 – Known Standard Deviation
- Confidence Intervals for One Standard Deviation with Tolerance Probability – Sample Standard Deviation
- Confidence Intervals for One Variance using Variance
- Confidence Intervals for One Variance using Relative Error
- Confidence Intervals for One Variance with Tolerance Probability – Known Variance
- Confidence Intervals for One Variance with Tolerance Probability – Sample Variance
- Confidence Intervals for the Ratio of Two Variances using Variances
- Confidence Intervals for the Ratio of Two Variances using Variances – Unequal n’s
- Confidence Intervals for the Ratio of Two Variances using Relative Error
- Confidence Intervals for the Ratio of Two Variances using Relative Error – Unequal n’s
- Quality Control Charts for Variability – R (Simulation)
- Quality Control Charts for Variability – S (Simulation)
- Quality Control Charts for Variability – S with Probability Limits (Simulation)
- Equivalence 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 Parallel Design
- Superiority by a Margin Tests for the Ratio of Two Within-Subject Variances in a Parallel Design
- 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
- Equivalence Tests for the Ratio of Two 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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

## Win-Ratio Composite Endpoint - 2 Scenarios

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

## Bayesian Adjustment

- Bayesian Adjustment using the Posterior Error Approach

## Tools

- Installation Validation Tool for Installation Qualification (IQ)
- Procedure Validation Tool for Operational Qualification (OQ)
- Chi-Square Effect-Size Estimator
- Multinomial Effect-Size Estimator
- Odds Ratio to Proportions Converter
- Probability Calculator (Various Distributions)
- Standard Deviation Estimator
- Survival Parameter Conversion Tool
- Standard Deviation of Means Calculator
- Data Simulator

## Design of Experiments (Non-Sample Size Tools)

These tools are used to generate designs, not to estimate or analyze sample size.- 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
- Randomization Lists