Maybe this is what you're looking for:
# x is your set of explanatory variables (10 of them):
x <- array(rnorm(1), dim=c(1000,10))
# y is your dependent variable:
y <- rbinom(1000, 1, 0.3)
# run the regression on each column of x:
reg <- apply(x, 2, function(z) glm(y ~ z, family=binomial(lin
So in my first try before I got your message, this is what I did:
orconf<-list()
ccoef<-list()
or<-list()
coef<-list()
out<-list()
for (i in 1:49){
out[[i]]<-glm(y~var[[i]],family=binomial(link="logit"))
coef[[i]]<-out[[i]]$coef[2]
or[[i]]<-exp(out[[i]]$coef[2])
bond<-matrix(out[[i]]$coef[2
Not knowing what format your data is in or what model you are using...
df # is your data frame with columns the variables you are running regressions
for
datout <- data.frame(coeff = NA, conf_low = NA, conf_high = NA, odd = NA) # a
table to put your results in
for(i in 1:length(names(df)[2:10]))
I have never made a loop on my own to do anything in R. But I am hoping
someone can help me build one for the following issue:
I need to make a univariate logistic regression for each of my variables
(about 62 of them), then I need to gather up each of their coefficients (not
the intercepts), eac
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