问题
I would like to run the dependent variable of a logistic regression (in my data set it's : dat$admit
) with all available variables, each regression with its own Independent variable vs dependent variable. The outcome that I wanted to get back is a list of each regression summary : coeff,p-value ,AUC. Using the data set submitted below there should be 3 regressions.
Here is a sample data set (where admit is the logistic regression dependent variable) :
>dat <- read.table(text = " female apcalc admit num
+ 0 0 0 7
+ 0 0 1 1
+ 0 1 0 3
+ 0 1 1 7
+ 1 0 0 5
+ 1 0 1 1
+ 1 1 0 0
+ 1 1 1 6",
+ header = TRUE)
I have this function that present a list of each regression and the coef but I don't find a way to bind also AUC and p value. Here is the code:
t(sapply(setdiff(names(dat),"admit"), function(x) coef(glm(reformulate(x,response="admit"), data=dat,family=binomial))))
Any idea how to create this list? Thanks, Ron
回答1:
Try
library(caTools)
ResFunc <- function(x) {
temp <- glm(reformulate(x,response="admit"), data=dat,family=binomial)
c(summary(temp)$coefficients[,1],
summary(temp)$coefficients[,4],
colAUC(predict(temp, type = "response"), dat$admit))
}
temp <- as.data.frame(t(sapply(setdiff(names(dat),"admit"), ResFunc)))
colnames(temp) <- c("Intercept", "Estimate", "P-Value (Intercept)", "P-Value (Estimate)", "AUC")
temp
# Intercept Estimate P-Value (Intercept) P-Value (Estimate) AUC
# female 0.000000e+00 0.000000e+00 1 1 0.5
# apcalc 0.000000e+00 0.000000e+00 1 1 0.5
# num 5.177403e-16 -1.171295e-16 1 1 0.5
来源:https://stackoverflow.com/questions/22742887/loop-that-will-run-a-logistic-regression-across-all-independent-variables-and-pr