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])) {
fit <- glm(data[,1] ~ data[,i], data = df, etc...)
datout[i,] <- fit[e.g, 1:4] # determine what values in your model output are what you need
}
datout # a table with all your output for each variable

On Sunday, May 8, 2011 at 11:58 AM, SevannaD wrote:

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), each of their 95% confidence intervals, and each of thier
> odds ratios and place them in a matrix to showcase them for my thesis. 
> 
> currently, I am writing them all out one by one with the cbond method, which
> has taken me a better part of a day so far and I know there has to be able
> to be a way to make a loop that can do this whole process, I just havent
> been able to figure it out yet.
> 
> Thanks in advance. 
> 
> --
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