t_test_two_sample: Generate two-sample t-test results for multiple sub-groups

In roistats: Convenience Functions for Applying Basic Stats to Sub-Groups

Description

This function produce two-sample t-test (two-tailed with confident interval at 0.95) results for multiple sub-groups and provides with a nice output in a table format. It can also add adjusted p values for multiple comparison issue.

Usage

t_test_two_sample(data, x, y, paired = FALSE, p_adjust = "bonferroni")

Arguments

data	A grouped data frame. It should be grouped by the intended sub-groups which you want to do the same t-test.
x	Column name of the variable which contains data values that you want to test (see t.test and details).
y	Column name of the variable which contains data values of group assignments for the test values (see t.test and details).
paired	a logical indicating whether you want a paired t-test.
p_adjust	character indicating which method should be used for adjusting multiple comparisons (see p.adjust and details). The default "bonferroni" corresponds to Bonferroni adjustment.

Value

A data.frame with the t-statistics table consisting of characters. The columns that are always present are: group variable(s), tvalue, df (degrees of freedom), p, and p_adjustmethod(s).

Examples

t_test_two_sample(color_index_two_sample, x = "color_effect", y = "group", paired = TRUE)

# use bonferroni and fdr method for adjusted p values.
library(magrittr)
color_index_two_sample %>%
  t_test_two_sample(
  x = "color_effect", y = "group", paired = TRUE, p_adjust = c("bonferroni","fdr")
  )

roistats documentation built on March 11, 2021, 1:07 a.m.