R 当我们有很多变量时，如何处理测试依赖性

我想使用在R中实现的卡方检验来测试许多分类变量的依赖性。事实上，我有14个变量，对所有变量进行14*14的测试非常长。正如你所知，卡方检验只涉及在正常情况下对两个变量进行测试，就像这样，当我需要测试

TYPE\u PEAU

和

sensitive

之间的依赖关系时

> library(MASS)
> tbl = table(DATA_BASE$TYPE_PEAU, DATA_BASE$SENSIBILITE)
> chisq.test(tbl)

    Pearson's Chi-squared test

data:  tbl
X-squared = 5727.5, df = 12, p-value < 2.2e-16

---

提前感谢

这似乎不是一个适合堆栈溢出的特定编程问题。如果您对各种统计方法的适当使用有一般性问题，那么您应该在上询问这些问题。你更有可能在那里得到更好的答案。或者澄清一下你所说的“很长”和“我该如何处理它们”的意思，请检查@A.Suliman，非常感谢！这就是我需要的

> dput(DATA_BASE[1:50,15:18])
structure(list(TYPE_PEAU = structure(c(3L, 4L, 5L, 1L, 3L, 1L, 
1L, 1L, 3L, 1L, 1L, 1L, 4L, 3L, 1L, 3L, 1L, 3L, 3L, 3L, 1L, 1L, 
1L, 3L, 1L, 1L, 3L, 1L, 3L, 5L, 1L, 5L, 2L, 1L, 5L, 5L, 3L, 1L, 
3L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 3L, 1L), .Label = c("", 
"Grasse", "Mixte", "Normale", "Sèche"), class = "factor"), SENSIBILITE = structure(c(4L, 
4L, 4L, 1L, 3L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 4L, 4L, 1L, 3L, 1L, 
3L, 3L, 4L, 1L, 1L, 1L, 2L, 1L, 1L, 4L, 1L, 2L, 3L, 1L, 4L, 4L, 
1L, 3L, 4L, 4L, 1L, 4L, 1L, 1L, 1L, 1L, 4L, 1L, 1L, 1L, 1L, 4L, 
1L), .Label = c("", "Aucune", "Fréquente", "Occasionnelle"), class = "factor"), 
    IMPERFECTIONS = structure(c(3L, 4L, 3L, 1L, 2L, 1L, 1L, 1L, 
    4L, 1L, 1L, 1L, 3L, 3L, 1L, 2L, 1L, 3L, 2L, 3L, 1L, 1L, 1L, 
    4L, 1L, 1L, 3L, 1L, 3L, 2L, 1L, 4L, 3L, 1L, 3L, 3L, 3L, 1L, 
    2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 3L, 1L), .Label = c("", 
    "Fréquente", "Occasionnelle", "Rares"), class = "factor"), 
    BRILLANCE = structure(c(4L, 2L, 2L, 1L, 4L, 1L, 1L, 1L, 4L, 
    1L, 1L, 1L, 4L, 4L, 1L, 4L, 1L, 4L, 4L, 4L, 1L, 1L, 1L, 4L, 
    1L, 1L, 4L, 1L, 4L, 4L, 1L, 2L, 3L, 1L, 4L, 4L, 4L, 1L, 4L, 
    1L, 1L, 1L, 1L, 4L, 1L, 1L, 1L, 1L, 4L, 1L), .Label = c("", 
    "Aucune", "Partout", "Zone T"), class = "factor")), .Names = c("TYPE_PEAU", 
"SENSIBILITE", "IMPERFECTIONS", "BRILLANCE"), row.names = c(15L, 
22L, 33L, 40L, 48L, 54L, 59L, 65L, 74L, 78L, 87L, 89L, 104L, 
108L, 115L, 121L, 141L, 159L, 161L, 163L, 165L, 175L, 179L, 186L, 
196L, 202L, 211L, 222L, 231L, 265L, 272L, 290L, 300L, 318L, 325L, 
327L, 349L, 372L, 374L, 380L, 392L, 393L, 394L, 398L, 427L, 440L, 
449L, 450L, 456L, 470L), class = "data.frame")