r - 来自方差分析输出的 x 和 y 变量的 p 值矩阵

Question

我有很多 X 和 Y 变量(比如 500 x 500)。以下只是小数据:

yvars <- data.frame (Yv1 = rnorm(100, 5, 3), Y2 = rnorm (100, 6, 4),
  Yv3 = rnorm (100, 14, 3))
xvars <- data.frame (Xv1 = sample (c(1,0, -1), 100, replace = T),
 X2 = sample (c(1,0, -1), 100, replace = T), 
 Xv3 = sample (c(1,0, -1), 100, replace = T), 
 D = sample (c(1,0, -1), 100, replace = T))

我想提取 p 值并制作这样的矩阵:

     Yv1    Y2     Yv3   
Xv1
X2
Xv3
D

这是我尝试循环该过程:

prob = NULL
   anova.pmat <- function (x) {
            mydata <- data.frame(yvar = yvars[, x], xvars)
            for (i in seq(length(xvars))) {
              prob[[i]] <- anova(lm(yvar ~ mydata[, i + 1],
              data = mydata))$`Pr(>F)`[1]
              }
              }
    sapply (yvars,anova.pmat)
    Error in .subset(x, j) : only 0's may be mixed with negative subscripts
What could be the solution ?

编辑:

对于第一个 Y 变量:

对于第一个 Y 变量:

prob <- NULL
 mydata <- data.frame(yvar = yvars[, 1], xvars)
for (i in seq(length(xvars))) {
              prob[[i]] <- anova(lm(yvar ~ mydata[, i + 1],
              data = mydata))$`Pr(>F)`[1]
              }

prob 
[1] 0.4995179 0.4067040 0.4181571 0.6291167

再次编辑:

for (j in seq(length (yvars))){
        prob <- NULL
        mydata <- data.frame(yvar = yvars[, j], xvars)
         for (i in seq(length(xvars))) {
                  prob[[i]] <- anova(lm(yvar ~ mydata[, i + 1],
                  data = mydata))$`Pr(>F)`[1]
                  }
}

Gives the same result as above !!!

Answer 1

这是一种使用 plyr 的方法为每个 xvars 循环遍历数据帧的列(将其视为列表)和 yvars ，返回适当的 p 值，将其排列成矩阵。添加行/列名称只是额外的。

library("plyr")

probs <- laply(xvars, function(x) {
    laply(yvars, function(y) {
        anova(lm(y~x))$`Pr(>F)`[1]
    })
})
rownames(probs) <- names(xvars)
colnames(probs) <- names(yvars)