为每组中的每一行运行一个 wilcox 函数

问题描述

我有一个如下的数据框:

I have a dataframe as follows:

df <- data.frame(group = c("A", "B", "C", "D", "E"),
                 country=c("US","UK"),
                 md = runif(10,0,10),
                 og = runif(10, 0, 10))

并希望在每一行中应用 wilcox 函数来比较每个组和每个国家的 md 和 og.

and want to apply wilcox function in each row to compare md and og in each group and each country.

results <- apply(df,1,function(x){
 df <- data.frame(x)
 wres<-wilcox.test(df$md,df$og)
 df$test<-format(wres$p.value,scientific = F)
 })

我想要另一列包含 P 值.但是当我运行它时，它给了我以下错误:

I want to have another column consists of P-value.but when I run it it gives me the following error:

Error in wilcox.test.default(df$mean_modified, df$mean_original) :
  'x' must be numeric

推荐答案

我们可以使用 mapply 对每个值应用 wilcox.test 然后提取 p.value 来自它

We can use mapply to apply wilcox.test for every value and then extract p.value from it

df$p.value <- mapply(function(x, y) wilcox.test(x, y)$p.value, df$md, df$og)

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