带RStatix的Wilcoxon环内检验

rstatix旨在很好地适应基于Tidyverse的工作流和管道，因此，您可以首先将数据集旋转到更长，分组并将分组的tibble传递到wilcox_test()，而不是循环:

library(rstatix)
library(dplyr)
library(tidyr)

grp1 <- runif(10, min = 0, max = 100)  # Exemple de données numériques
grp2 <- runif(10, min = 0, max = 100)
grp3 <- runif(10, min = 0, max = 100)
grp4 <- runif(10, min = 0, max = 100)
status <- sample(c("alive", "death", "sick"), 10, replace = TRUE)  # Exemple de données caractère
my_data_frame <- data.frame(grp1, grp2, grp3, grp4, status)

my_data_frame |>
  pivot_longer(-status, names_to = "grp") |>
  group_by(grp) |>
  wilcox_test(value ~ status, p.adjust.method = "fdr")
#> # A tibble: 12 × 10
#>    grp   .y.   group1 group2    n1    n2 statistic     p p.adj p.adj.signif
#>  * <chr> <chr> <chr>  <chr>  <int> <int>     <dbl> <dbl> <dbl> <chr>       
#>  1 grp1  value alive  death      3     3         3 0.7   0.857 ns          
#>  2 grp1  value alive  sick       3     4         3 0.4   0.857 ns          
#>  3 grp1  value death  sick       3     4         5 0.857 0.857 ns          
#>  4 grp2  value alive  death      3     3         3 0.7   0.7   ns          
#>  5 grp2  value alive  sick       3     4         8 0.629 0.7   ns          
#>  6 grp2  value death  sick       3     4        12 0.057 0.171 ns          
#>  7 grp3  value alive  death      3     3         7 0.4   0.629 ns          
#>  8 grp3  value alive  sick       3     4         8 0.629 0.629 ns          
#>  9 grp3  value death  sick       3     4         4 0.629 0.629 ns          
#> 10 grp4  value alive  death      3     3         3 0.7   0.7   ns          
#> 11 grp4  value alive  sick       3     4         4 0.629 0.7   ns          
#> 12 grp4  value death  sick       3     4         8 0.629 0.7   ns

^{创建于2024-02-09年第reprex v2.1.0页}