1

我有一个函数可以使用 wilcoxon 测试比较每组中的列。功能：

group.leb=c(1,2)
z <- c(2,3,4)
v <- 2
s <- sapply(z,'+',v)
combination <- mapply(c,z,s,SIMPLIFY = F)



wilcox.fun <- function(dat) { 
  do.call(rbind, lapply(combination, function(x) {
    test <- wilcox.test(dat[[x[1]]], dat[[x[2]]], paired=FALSE)
    data.frame(Test = sprintf('Group %s by Group %s', x[1], x[2]), 
               W = round(test$statistic,4), 
               p = test$p.value)
  }))
}

result <- purrr::map_df(split(data, data$group), wilcox.fun, .id = 'Group')

我想设置一个参数，以便函数对某些组计数，而不是连续计数。

我想得到什么

|   Group|
|--------|
|  1     |
|  1     |
|  1     |
|  3     |
|  3     |
|  3     |

或另一个订单，例如：（2 和 3）

我的数据框：

data <- structure(list(group = c(1L, 1L, 1L, 1L, 1L, 1L,1L,1L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), col1 = c(9, 
9.05, 7.15, 7.21, 7.34, 8.12, 7.5, 7.84, 7.8, 7.52, 8.84, 6.98, 
6.1, 6.89, 6.5, 7.5, 7.8, 5.5, 6.61, 7.65, 7.68,8.0,9.0), col2 = c(11L, 
11L, 10L, 1L, 3L, 7L, 11L, 11L, 11L, 11L, 4L, 1L, 1L, 1L, 2L, 
2L, 1L, 4L, 8L, 8L, 1L,3L,4L), col3 = c(7L, 11L, 3L, 7L, 11L, 2L, 11L, 
5L, 11L, 11L, 5L, 11L, 11L, 2L, 9L, 9L, 3L, 8L, 11L, 11L, 2L,5L,6L), 
    col4 = c(11L, 11L, 11L, 11L, 6L, 11L, 11L, 11L, 10L, 7L, 
    11L, 2L, 11L, 3L, 11L, 11L, 6L, 11L, 1L, 11L, 11L,13L,12L), col5 = c(11L, 
    1L, 2L, 2L, 11L, 11L, 1L, 10L, 2L, 11L, 1L, 3L, 11L, 11L, 
    8L, 8L, 11L, 11L, 11L, 2L, 9L,4L,5L)), .Names = c("group", "col1", 
"col2", "col3", "col4", "col5"), class = "data.frame", row.names = c(NA, 
-21L))
4

1 回答 1

1

这是在耍花招吗？

wilcox.fun <- function(df, id_group){
  df = df[df$group%in%id_group,]
 x <- function(dat) { 
  do.call(rbind, lapply(combination, function(x) {
    test <- wilcox.test(dat[[x[1]]], dat[[x[2]]], paired=FALSE)
    data.frame(Test = sprintf('Group %s by Group %s', x[1], x[2]), 
               W = round(test$statistic,4), 
               p = test$p.value)
  }))
 }
 return (purrr::map_df(split(df, df$group), x, .id = 'Group'))
}


wilcox.fun(data, c(1,3))

输出 ：

       Group               Test    W          p
W...1      1 Group 2 by Group 4 40.0 0.42919530
W1...2     1 Group 3 by Group 5 20.0 0.14199085
W2...3     1 Group 4 by Group 6 38.5 0.51567473
W...4      3 Group 2 by Group 4 33.0 0.95802933
W1...5     3 Group 3 by Group 5  9.0 0.01679008
W2...6     3 Group 4 by Group 6 28.0 0.70822798
于 2021-08-09T09:18:24.243 回答