Question

如果我以这种方式定义modelList，我可以提取p值（df2）

responseList <- names(mtcars)[-c(4,9)]
modelList    <- lapply(responseList, function(resp) {
                           mF <- formula(paste(resp, " ~ hp*am"))
                           aov(mF, data = mtcars)
                })
df2 <- plyr::ldply( modelList , function(x) summary(x)[[1]][["Pr(>F)"]])
names(df2) <- c(attr(modelList[[1]]$terms, "term.labels"), "residuals")

但是如果我按以下方式定义ModelList，我就无法得到结果。

formula <- as.formula(paste0("cbind(", paste(names(mtcars)[-c(4,9)], collapse = ","), ") ~ hp*am"))
modelList  <- aov(formula, data=mtcars)

那么如何修改df2以便从modelList的第二个定义函数中提取pvalues。

df2 <- plyr::ldply( modelList , function(x) summary(x)[[1]][["Pr(>F)"]])
    names(df2) <- c(attr(modelList[[1]]$terms, "term.labels"), "residuals")

Answer 1

以下是从第二个formula <- as.formula(paste0("cbind(", paste(names(mtcars)[-c(4,9)], collapse = ","), ") ~ hp*am")) modelList2 <- aov(formula, data=mtcars) df2 <- plyr::ldply( summary(modelList2), function(x) x[,"Pr(>F)"]) names(df2) <- c("", rownames(modelList2[[1]])[-1], "residuals") df2 ################ hp am hp:am residuals 1 Response mpg 1.504500e-09 4.748593e-05 0.9806460396 NA 2 Response cyl 3.974632e-11 2.997217e-04 0.0969093688 NA 3 Response disp 5.835767e-11 1.164601e-05 0.0178673463 NA 4 Response drat 9.236405e-04 1.911898e-05 0.8664040719 NA 5 Response wt 1.348501e-07 2.977105e-06 0.1913211750 NA 6 Response qsec 2.312064e-07 4.577810e-04 0.1767439339 NA 7 Response vs 2.060911e-06 9.495711e-01 0.0458841894 NA 8 Response gear 1.696824e-01 1.405025e-09 0.0002293635 NA 9 Response carb 3.077405e-07 3.622291e-02 0.1902486095 NA中提取p值的可能方法之一。

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如何修改p值的代码（lapply R）

1 个答案: