Re: [R] Running regression (lm, lrm) 100+ times and saving the results as matrix

From: Mike H. Ryu <hokyung.ryu_at_yale.edu>
Date: Tue, 29 Apr 2008 19:38:09 -0400

Much thanks to Chuck Cleland for the following solution:

t(sapply(split(mydf, mydf$TIME), function(x){coefficients(summary(glm(X ~ A + B, data = x, family=binomial)))}))

To see what's in the 12 columns of the matrix returned by those lines, look at the results this way:

lapply(split(mydf, mydf$TIME), function(x){coefficients(summary(glm(X ~ A + B, data = x, family=binomial)))})

-----Original Message-----
From: r-help-bounces_at_r-project.org [mailto:r-help-bounces_at_r-project.org] On Behalf Of Mike H. Ryu
Sent: Tuesday, April 29, 2008 7:27 AM
To: r-help_at_r-project.org
Subject: [R] Running regression (lm, lrm) 100+ times and saving the results as matrix

An undergraduate here, so do not hesitate to let me know if you feel that I'm heading in a wrong direction.  

I have a data frame containing panel data across 10 years (hence 120 months). I want to be able to run regression separately for each month (or year). The below shows how I ran the regression for each month, but I need to know how I would combine the regression results together into a matrix possibly.  

Thank you!  

Mike  


m = max(data$TIME)

# define regmatrix  

for(i in 1:m){

 g=runreg(data, i)

 # attach g to regmatrix

}
 

runreg = function(data, index){

datainterim = subset(data, TIME==index)

g = lrm(X ~ A + B, datainterim)

return(g)

}

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Wed 30 Apr 2008 - 00:42:03 GMT

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