在多对列上提取和格式化cor.test的结果 [英] Extracting and formatting results of cor.test on multiple pairs of columns

问题描述

我正在尝试生成相关矩阵的表输出。具体来说，我使用一个for循环来识别第4:40列到第1列中所有数据之间的相关性。虽然表的结果不错，但它不识别正在比较的内容什么。在检查 cor.test 的属性时，我发现data.name被指定为 x [1] 和 y [1] 不足以追溯到哪个列与哪个列进行比较。这是我的代码：

I am trying to generate a table output of a correlation matrix. Specifically, I am using a for loop in order to identify a correlation between all data in columns 4:40 to column 1. While the results of the table are decent, it does not identify what is being compared to what. In checking attributes of cor.test,I find that data.name is being given as x[1] and y[1] which is not good enough to trace back which columns is being compared to what. Here is my code:

input <- read.delim(file="InputData.txt", header=TRUE)
x<-input[,41, drop=FALSE]
y=input[,4:40]
corr.values <- vector("list", 37)
for (i in 1:length(y) ){
  corr.values[[i]] <- cor.test(x[[1]], y[[i]], method="pearson")
}
lres <- sapply(corr.values, `[`, c("statistic","p.value","estimate","method", "data.name"))
lres<-t(lres)
write.table(lres, file="output.xls", sep="\t",row.names=TRUE)

输出文件如下：

       statistic        p.value     estimate                                  method            data.name   
1   -2.030111981    0.042938137 -0.095687495    Pearson's product-moment correlation    x[[1]] and y[[i]]
2   -2.795786248    0.005400938 -0.131239287    Pearson's product-moment correlation    x[[1]] and y[[i]]
3   -2.099114632    0.036368337 -0.098908573    Pearson's product-moment correlation    x[[1]] and y[[i]]
4   -1.920649487    0.055413178 -0.090571599    Pearson's product-moment correlation    x[[1]] and y[[i]]
5   -1.981326962    0.048168291 -0.093408365    Pearson's product-moment correlation    x[[1]] and y[[i]]
6   -2.80390736      0.00526909 -0.131613912    Pearson's product-moment correlation    x[[1]] and y[[i]]
7   -1.265138839    0.206482153 -0.059798855    Pearson's product-moment correlation    x[[1]] and y[[i]]
8   -2.861448156    0.004415411 -0.134266636    Pearson's product-moment correlation    x[[1]] and y[[i]]
9   -2.103403363    0.035990039 -0.099108672    Pearson's product-moment correlation    x[[1]] and y[[i]]
10  -3.610094985    0.000340807 -0.168498786    Pearson's product-moment correlation    x[[1]] and y[[i]]

很显然，由于行编号和无法分辨出与哪个相关。有没有办法来解决这个问题？我尝试了许多解决方案，但都没有成功。我知道诀窍一定是编辑 data.name 属性，但是我不知道该怎么做。

Clearly, this is not perfect as rows are numbered and can't tell which correlation is to what. Is there a way to fix this? I tried many solutions but none worked.I know that the trick must be in editing the data.name attribute however I couldn't figure out how to do that.

推荐答案

这是一种返回具有所有 cor.test 结果的数据框的方法其中还包括针对每个相关性进行计算的变量的名称：我们创建一个函数来提取 cor.test 的相关结果，然后使用 mapply 将该函数应用于我们想要相关的每对变量。 mapply 返回一个列表，因此我们使用 do.call（rbind，...）将其转换为数据

Here's a way to return a data frame with all the cor.test results that also includes the names of the variables for which each correlation was calculated: We create a function to extract the relevant results of cor.test then use mapply to apply the function to each pair of variables for which we want the correlations. mapply returns a list, so we use do.call(rbind, ...) to turn it into a data frame.

# Function to extract correlation coefficient and p-values
corrFunc <- function(var1, var2, data) {
  result = cor.test(data[,var1], data[,var2])
  data.frame(var1, var2, result[c("estimate","p.value","statistic","method")], 
             stringsAsFactors=FALSE)
}

## Pairs of variables for which we want correlations
vars = data.frame(v1=names(mtcars)[1], v2=names(mtcars)[-1])

# Apply corrFunc to all rows of vars
corrs = do.call(rbind, mapply(corrFunc, vars[,1], vars[,2], MoreArgs=list(data=mtcars), 
                              SIMPLIFY=FALSE))

     var1 var2   estimate      p.value statistic                               method
cor   mpg  cyl -0.8475514 9.380327e-10 -8.747152 Pearson's product-moment correlation
cor1  mpg disp -0.7761684 1.787835e-07 -6.742389 Pearson's product-moment correlation
cor2  mpg   hp  0.4186840 1.708199e-02  2.525213 Pearson's product-moment correlation
cor3  mpg drat  0.6811719 1.776240e-05  5.096042 Pearson's product-moment correlation
cor4  mpg   wt  0.4802848 5.400948e-03  2.999191 Pearson's product-moment correlation
cor5  mpg qsec  0.6640389 3.415937e-05  4.864385 Pearson's product-moment correlation
cor6  mpg   vs  0.5998324 2.850207e-04  4.106127 Pearson's product-moment correlation
cor7  mpg   am  1.0000000 0.000000e+00       Inf Pearson's product-moment correlation
cor8  mpg gear -0.8676594 1.293959e-10 -9.559044 Pearson's product-moment correlation
cor9  mpg carb -0.8521620 6.112687e-10 -8.919699 Pearson's product-moment correlation

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