test.tmulti: Multiple pairwise comparisons with diagnostics

In autotestR: Automated Functions for Basic Statistical Tests

Multiple pairwise comparisons with diagnostics

Description

Performs multiple pairwise comparisons using Student's t-test or Mann-Whitney test, with automatic diagnostics, effect sizes, confidence intervals, multiple testing correction and visualization.

Usage

test.tmulti(
  ...,
  comparisons = NULL,
  title = "Multiple comparisons (t / MW)",
  xlab = "",
  ylab = "Value",
  style = c("boxplot", "violin", "mono", "halfeye"),
  p_adjust = c("none", "holm", "BH", "bonferroni"),
  help = FALSE,
  verbose = TRUE
)

Arguments

...	Numeric vectors or a data.frame with groups in columns.
comparisons	List of character vectors specifying pairwise comparisons (e.g. list(c("A","B"), c("B","C"))). If NULL, all pairwise combinations are used.
title	Plot title.
xlab	X-axis label.
ylab	Y-axis label.
style	Plot style. One of "boxplot", "violin", "mono", or "halfeye".
p_adjust	Method for multiple testing correction. One of "none", "holm", "BH", "bonferroni".
help	Logical. If TRUE, prints usage examples.
verbose	Logical. If TRUE, prints results and plots.

Details

Normality is assessed using Shapiro-Wilk tests and homogeneity of variances using Levene's test. If assumptions are met, a pooled-variance t-test is used. Otherwise, the Mann-Whitney test is applied with bootstrap confidence intervals.

Effect sizes:

• Cohen's d for t-tests

• Rank-biserial correlation for Mann-Whitney

Value

A list with:

results

A tibble with test results.

plot

A ggplot object.

data_long

Long-format data used for plotting.

Examples

df <- data.frame(
  control   = rnorm(30, 10),
  treatment = rnorm(30, 12),
  test1     = rnorm(30, 11),
  test2     = rnorm(30, 15)
)

test.tmulti(
  df,
  comparisons = list(
    c("control", "treatment"),
    c("treatment", "test1")
  )
)

autotestR documentation built on April 29, 2026, 1:09 a.m.