How to Perform Paired Pairwise T-tests in R

Prerequisites

# Load required R packages
library(tidyverse)
library(rstatix)
library(ggpubr)

Data preparation

We’ll use the self-esteem score dataset measured over three time points. The data is available in the datarium package.

# Wide format
data("selfesteem", package = "datarium")
head(selfesteem, 3)

## # A tibble: 3 x 4
##      id    t1    t2    t3
##   <int> <dbl> <dbl> <dbl>
## 1     1  4.01  5.18  7.11
## 2     2  2.56  6.91  6.31
## 3     3  3.24  4.44  9.78

# Gather columns t1, t2 and t3 into long format
# Convert id and time into factor variables
selfesteem <- selfesteem %>%
  gather(key = "time", value = "score", t1, t2, t3) %>%
  convert_as_factor(id, time)
head(selfesteem, 3)

## # A tibble: 3 x 3
##   id    time  score
##   <fct> <fct> <dbl>
## 1 1     t1     4.01
## 2 2     t1     2.56
## 3 3     t1     3.24

Run paired pairwise t-tests

You can perform multiple pairwise paired t-tests between the levels of the within-subjects factor (here time). P-values are adjusted using the Bonferroni multiple testing correction method.

stat.test <- selfesteem %>%
  pairwise_t_test(
    score ~ time, paired = TRUE,
    p.adjust.method = "bonferroni"
    )
stat.test

## # A tibble: 3 x 10
##   .y.   group1 group2    n1    n2 statistic    df           p    p.adj p.adj.signif
## * <chr> <chr>  <chr>  <int> <int>     <dbl> <dbl>       <dbl>    <dbl> <chr>       
## 1 score t1     t2        10    10     -4.97     9 0.000772    0.002    **          
## 2 score t1     t3        10    10    -13.2      9 0.000000334 0.000001 ****        
## 3 score t2     t3        10    10     -4.87     9 0.000886    0.003    **

Visualization: box plots with p-values

# Create the plot
myplot <- ggboxplot(selfesteem, x = "time", y = "score", add = "point")
# Add statistical test p-values
stat.test <- stat.test %>% add_xy_position(x = "time")
myplot + stat_pvalue_manual(stat.test, label = "p.adj.signif")