成对相关表 [英] Pairwise Correlation Table

问题描述

我是 R 的新手，所以如果这是一个简单的问题，我深表歉意，但是我今晚做了很多搜索，似乎无法弄清楚.我有一个包含大量变量的数据框，我想做的是创建一个这些子集之间的相关性表，基本上相当于 Stata 中的pwcorr"，或相关性"SPSS.对此的一个关键是，我不仅想要 r，而且还想要与该值相关的重要性.

I'm new to R, so I apologize if this is a straightforward question, however I've done quite a bit of searching this evening and can't seem to figure it out. I've got a data frame with a whole slew of variables, and what I'd like to do is create a table of the correlations among a subset of these, basically the equivalent of "pwcorr" in Stata, or "correlations" in SPSS. The one key to this is that not only do I want the r, but I also want the significance associated with that value.

有什么想法吗?这看起来应该很简单，但我似乎想不出什么好方法.

Any ideas? This seems like it should be very simple, but I can't seem to figure out a good way.

推荐答案

Bill Venables 在 这个答案 来自 R 邮件列表，我对其做了一些轻微的修改:

Bill Venables offers this solution in this answer from the R mailing list to which I've made some slight modifications:

cor.prob <- function(X, dfr = nrow(X) - 2) {
  R <- cor(X)
  above <- row(R) < col(R)
  r2 <- R[above]^2
  Fstat <- r2 * dfr / (1 - r2)
  R[above] <- 1 - pf(Fstat, 1, dfr)

  cor.mat <- t(R)
  cor.mat[upper.tri(cor.mat)] <- NA
  cor.mat
}

让我们测试一下:

set.seed(123)
data <- matrix(rnorm(100), 20, 5)
cor.prob(data)

          [,1]      [,2]      [,3]      [,4] [,5]
[1,] 1.0000000        NA        NA        NA   NA
[2,] 0.7005361 1.0000000        NA        NA   NA
[3,] 0.5990483 0.6816955 1.0000000        NA   NA
[4,] 0.6098357 0.3287116 0.5325167 1.0000000   NA
[5,] 0.3364028 0.1121927 0.1329906 0.5962835    1

这与 cor.test 一致吗?

Does that line up with cor.test?

cor.test(data[,2], data[,3])

 Pearson's product-moment correlation
data:  data[, 2] and data[, 3] 
t = 0.4169, df = 18, p-value = 0.6817
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.3603246  0.5178982 
sample estimates:
       cor 
0.09778865 

似乎工作正常.

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