Compare curves with the log-rank test (including test for trend)Ĭomparison of data from nested data tables using nested t test or nested one-way ANOVA (using mixed effects model).įit one of our 105 built-in equations, or enter your own. Three-way ANOVA (limited to two levels in two of the factors, and any number of levels in the third).Īnalysis 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).

Two-way ANOVA, even with missing values with some post tests. Calculate the relative risk and odds ratio with confidence intervals. Kruskal-Wallis or Friedman nonparametric one-way ANOVA with Dunn’s post test.įisher’s exact test or the chi-square 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. Reports P values and confidence intervals.Īutomatically generate volcano plot (difference vs.

Pad prism