在 purrr 的 map() 函数中使用 levene_test 吗？

有没有办法通过进行 Levene 测试map()函数从purrr包裹？或者是否有另一种简单的方法来计算各种变量的 Levene 检验？

我的数据框包含各种因子和数字列，所以我尝试使用map_if()，效果很好，例如，对于夏皮罗检验。但是，我不知道如何指定公式。我想根据“治疗”因素测试所有数值变量。

library("tidyverse")
library("rstatix")

data <- data.frame(site = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), 
                                    .Label = c("S1 ", "S2 ", "S3 "), class = "factor"), 
                   plot = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L), 
                                    .Label = c(" Tree 1 ", " Tree 2 ", " Tree 3 "), class = "factor"), 
                   Treatment = structure(c(2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L), .Label = c("T1", "T2"), class = "factor"), 
                   flux1 = c(11.52188065, 8.43156699, 4.495312274, -1.866676811, 3.861102035, -0.814742373, 6.51039536, 4.767950345, 10.36544542, 1.065963875), 
                   flux2 = c(0.142259208, 0.04060245, 0.807631744, 0.060127596, -0.157762562, 0.062464942, 0.043147603, 0.495001652, 0.34363348, 0.134183704), 
                   flux3 = c(0.147506197, 1.131009714, 0.038860728, 0.0176834, 0.053191593, 0.047591306, 0.00573377, -0.034926075, 0.123379247, 0.018882469))

map_if(data, is.numeric, levene_test(. ~ Treatment))

有什么建议么？感谢您的帮助！

现在还有一个可重现的示例；）

这是一个替代方案： 首先转向长数据，

Then group_by并应用公式（这里通量应该是因子！）

library(tidyr)
library(dplyr)

data %>% 
  pivot_longer(
    cols = starts_with("flux"),
    names_to = "flux",
    values_to = "value"
  ) %>%
  mutate(flux = as.factor(flux)) %>% 
  group_by(flux) %>% 
  levene_test(value ~ Treatment)

  flux    df1   df2 statistic     p
  <fct> <int> <int>     <dbl> <dbl>
1 flux1     1     8     0.410 0.540
2 flux2     1     8     2.85  0.130
3 flux3     1     8     1.11  0.323