These calculators perform power and sample size calculations for a variety of hypothesis tests.

Compare a mean, \(\mu\), to a known value, \(\mu_0\)

Compare the means from two groups using a parallel study design.

Compare the means from two groups using a crossover study design.

Compare the means from several groups using One-Way ANOVA. This calculator can be used for simultaneous or pairwise comparisons.

Compare the means from multiple groups using a multi-sample William's study design.

Compare a proportion, \(p\), to a known value, \(p_0\).

Compare proportions from two groups using a parallel study design.

Compare proportions from multiple groups using a crossover study design.

Compare an odds ratio to 1 using a parallel study design.

Compare an odds ratio to 1 using a crossover study design.

Compare a set of proportions using one-way ANOVA.

Compare the proportions from two groups using a multi-sample William's study design.

Compare a proportion, \(p\), to a known value, \(p_0\).

Compare proportions from two groups using a parallel study design using Fisher's Exact Test.

Compare the ratio of two survival curves.

Compare the difference of two hazard ratios estimated using an exponential time to event model.

Compare the total variability of two groups measured in a 2 by 2 crossover study.

Compare the total variability of two groups measured in a 2 by 2M crossover study.

Compare the total variability of two groups measured in a parallel study with replication within subjects.

Compare the total variability of two groups measured in a parallel study without replication within subjects.

Compare the intersubject variability within a group measured in a crossover study.

Compare the intersubject variability within a group measured in a parallel study.

Compare intrasubject variability measured in a crossover study.

Compare intrasubject variability measured in a parallel study.

Compare the intrasubject coefficient of variation (CV) within a group measured in a parallel study. This calculator supports both simple random effects and conditional random effects models to estimate the intrasubject CV.

Test the location of a sample using Wilcoxan signed rank test.

Test differences in the location of two sample using Wilcoxan rank sum test.

Test the value of Kendall's Coefficient.

Test the average bioequivalence of drugs using a 2 x 2 crossover design.

Test the population bioequivalence of drugs using using a 2 x 2 crossover design.

Test the existence of a carry-over effect in a 2 by 2 carryover design with a binary outcome. This calculator assumes the use of McNemar's test to test the hypothesis.

Test the independence of two categorical variables with multiple strata using the Cochran-Mantel-Haenszel Test.

Test the independence of two categorical variables using the Likelihood Ratio Test.

Test the existence of a categorical shift in a binary outcome evaluated using McNemar's Test.

Test a categorical variables goodness of fit compared to a reference distribution using Pearson's Goodness of Fit Test.

Test the independence of two categorical variables using the Pearson's Test of Independence.

Test the existance of a categorical shift in a binary outcome evaluated using the Stuart-Maxwell Test.

Test the normality of a sample based on a given distribution.

If there is a hypothesis that you will use but is not listed, let us know. We are always expanding our list of tools!