使用 perm.t.test 的多重配对排列 t 检验

Question

我有一些实验数据要用 R 分析，但我遇到了问题，经过几天的搜索，我找不到解决方案。

我需要对我的数据进行运行多重配对排列 t 检验。这是我的数据集的简化版本：

treat = c("C","C","C","C","C","C","C","C","C","C","C","C","C",
         "C","C","C","C","C","C","C","T","T","T","T","T","T",
         "T","T","T","T","T","T","T","T","T","T","T","T","T","T")
subj = c("B16","B17","B18","B19","B20","B16","B17","B18","B19",
        "B20","B16","B17","B18","B19","B20","B16","B17","B18",
        "B19","B20","B1","B2","B3","B4","B5","B1","B2","B3","B4"
        ,"B5","B1","B2","B3","B4","B5","B1","B2","B3","B4","B5")
t = c("T0","T0","T0","T0","T0","T1","T1","T1","T1","T1","T2",
      "T2","T2","T2","T2","T3","T3","T3","T3","T3","T0","T0",
      "T0","T0","T0","T1","T1","T1","T1","T1","T2","T2","T2",
      "T2","T2","T3","T3","T3","T3","T3")
exparat = c(0.11,0.27,0.04,0.47,-0.11,-0.05,-0.05,0.33,-0.11,
            0.47,-0.01,0.43,0.47,0.33,-0.11,-0.09,0.20,-0.11,
                0.47,0.33,0.19,0.02,0.33,0.47,-0.11,0.42,0.13,0.47,
                -0.11,0.33,0.42,0.19,-0.11,0.33,0.47,0.42,0.17,
                0.33,0.47,-0.11)

data = data.frame(treat, subj, t, exparat)

head(data)

  treat subj  t exparat
1     C  B16 T0    0.11
2     C  B17 T0    0.27
3     C  B18 T0    0.04
4     C  B19 T0    0.47
5     C  B20 T0   -0.11
6     C  B16 T1   -0.05

例如，我必须说明每次治疗 (treat) 的时间 (t) 组合之间的响应变量 (respvar) 是否存在差异。如果我必须使用参数 t 检验，我会使用 dplyr 管道和函数 group_by:

stat.test <- data %>%
  group_by(treat) %>%
  t_test(exparat ~ t, paired = TRUE)

但我不能对排列 t 检验（perm.t.test，包：RVAideMemoire）做同样的事情，因为它只允许对具有两个水平的因子进行检验。而我的因子时间 (t) 有 4 个级别。一种解决方案是为每一对时间 (t) 对我的数据进行子集化，如下所示：

perm.t.test(exparat~t,data = subset(data, t == "T1" | t == "T2"), nperm=999, paired = T)
perm.t.test(exparat~t,data = subset(data, t == "T1" | t == "T3"), nperm=999, paired = T)
perm.t.test(exparat~t,data = subset(data, t == "T2" | t == "T3"), nperm=999, paired = T)
perm.t.test(exparat~t,data = subset(data, t == "T1" | t == "T2"), nperm=999, paired = T)
perm.t.test(exparat~t,data = subset(data, t == "T1" | t == "T3"), nperm=999, paired = T)
perm.t.test(exparat~t,data = subset(data, t == "T2" | t == "T3"), nperm=999, paired = T)
    
#and so on

但这似乎是一种非常低效且耗时的方法。在我的真实数据集中，我确实有更多的因子 t 水平，所以设置所有这些需要很长时间。

任何人都可以帮我设置一个循环吗？

提前致谢。

Answer 1

您可以使用 combn 来获得 data$t 值的所有组合。

combn(levels(data$t), 2, function(x) {
  perm.t.test(exparat~t,data = subset(data, t %in% x), nperm=999, paired = T)
}, simplify = FALSE) -> result

result

使用 perm.t.test 的多重配对排列 t 检验

Multiple paired permutation t-tests using perm.t.test

r

dplyr

permutation

t-test