List of Sample Size Procedures – Over 650 Scenarios

This page contains a list of the tests and confidence intervals for which sample size and power can be calculated by PASS.  For a more in-depth look at the features of PASS, please download the free trial. Click to see some additional details about one or two means, multiple meanscorrelation, normality tests, variances, one proportion, two proportions, chi-square and other proportions tests, survival, or regression in PASS.

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Cluster-Randomized Designs - 25 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • Tests for Two Means from 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
  • 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 Two Proportions in a Cluster-Randomized Design using Differences
  • Superiority by a Margin Tests for Two Proportions in a Cluster-Randomized Design using Ratios

Conditional Power - 9 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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

Confidence Intervals - 85 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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 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 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 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 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

Correlation - 20 Scenarios

Click here to see additional details about correlation procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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

Cross-Over Designs - 15 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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
  • 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

Equivalence - 51 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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 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 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

Exponential Distribution Parameter Confidence Intervals - 4 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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 - 81 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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 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 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)

Means - One - 23 Scenarios

Click here to see additional details about one mean procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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 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
  • 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

Means - Two Correlated or Paired - 15 Scenarios

Click here to see additional details about paired means procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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
  • 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

Means - Two Independent - 91 Scenarios

Click here to see additional details about two independent means procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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
  • 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
  • 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
  • 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
  • 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 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
  • 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 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

Means - 2x2 Cross-Over Designs - 9 Scenarios

Click here to see additional details about cross-over designs for two means procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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

Means - Higher-Order Cross-Over Designs - 6 Scenarios

Click here to see additional details about cross-over designs for two means procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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

Means - Many (ANOVA) - 43 Scenarios

Click here to see additional details about multiple means procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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
  • 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)
  • 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
  • Randomized Block Analysis of Variance
  • Repeated Measures Analysis
  • Repeated Measures Analysis – Unequal n’s
  • MANOVA
  • MANOVA – Unequal n’s
  • Mixed Models
  • Mixed Models – Unequal n’s

Michaelis-Menten Parameters - 2 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

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

Non-Inferiority - 62 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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
  • 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 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)
  • 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

Nonparametric - 29 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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

Normality Tests - 9 Scenarios

Click here to see additional details about normality test procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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

Proportions - One - 47 Scenarios

Click here to see additional details about one proportion procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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
  • 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
  • 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

Proportions - Two Independent - 173 Scenarios

Click here to see additional details about two proportions procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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
  • 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)
  • 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

Proportions - Correlated or Paired - 7 Scenarios

Click here to see additional details about correlated proportions procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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
  • 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

Proportions - Many - 7 Scenarios

Click here to see additional details about chi-square and other proportions tests procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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
  • Logistic Regression
  • Tests for Two Ordered Categorical Variables
  • Tests for Two Ordered Categorical Variables – Unequal n’s

Quality Control - 12 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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 - 3 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • Poisson Means (Incidence Rates)
  • Post-Marketing Surveillance (Incidence Rates)
  • Poisson Regression

Regression - 10 Scenarios

Click here to see additional details about regression procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • Linear Regression
  • Confidence Intervals for Linear Regression Slope
  • Cox Regression
  • Logistic Regression
  • Multiple Regression
  • Poisson Regression
  • Probit Analysis - Probit
  • Probit Analysis – Logit
  • Confidence Intervals for Michaelis-Menten Parameters
  • Confidence Intervals for Michaelis-Menten Parameters – Unequal n’s

ROC Curves - 10 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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 - 16 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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

Superiority by a Margin Tests - 71 Scenarios

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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 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 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)
  • 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

Survival Analysis - 59 Scenarios

Click here to see additional details about survival procedures in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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
  • 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
  • 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

Variances and Standard Deviations - 28 Scenarios

Click here to see additional details about variances and standard deviations in PASS.

No other sample size software package provides the calculation scenarios highlighted in green.

  • 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)

Tools

  • 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

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