Comparison of data from nested data tables using nested t test or nested one-way ANOVA (using mixed effects model).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.Reports P values and confidence intervals.
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