Analysis of repeated measures data (one-, two-, and three-way) using a mixed effects model (similar to repeated measures ANOVA, but capable of handling missing data).
Three-way ANOVA (limited to two levels in two of the factors, and any number of levels in the third).
Tukey, Newman-Keuls, Dunnett, Bonferroni, Holm-Sidak, or Fisher’s LSD multiple comparisons testing main and simple effects.
Two-way ANOVA, with repeated measures in one or both factors.
Two-way ANOVA, even with missing values with some post tests.
Calculate the relative risk and odds ratio with confidence intervals.
Fisher's exact test or the chi-square test.
Kruskal-Wallis or Friedman nonparametric one-way ANOVA with Dunn's post test.
When this is chosen, multiple comparison tests also do not assume sphericity.
Greenhouse-Geisser correction so repeated measures one-, two-, and three-way ANOVA do not have to assume sphericity.
Many multiple comparisons test are accompanied by confidence intervals and multiplicity adjusted P values.
One-way ANOVA without assuming populations with equal standard deviations using Brown-Forsythe and Welch ANOVA, followed by appropriate comparisons tests (Games-Howell, Tamhane T2, Dunnett T3).
Ordinary or repeated measures ANOVA followed by the Tukey, Newman-Keuls, Dunnett, Bonferroni or Holm-Sidak multiple comparison tests, the post-test for trend, or Fisher’s Least Significant tests.
Perform many t tests at once, using False Discovery Rate (or Bonferroni multiple comparisons) to choose which comparisons are discoveries to study further.
Wilcoxon test with confidence interval of median.
Kolmogorov-Smirnov test to compare two groups.
Nonparametric Mann-Whitney test, including confidence interval of difference of medians.
Automatically generate volcano plot (difference vs.