Re: coef(summary(glm(extra ~ group, data=sleep[ rep(1:nrow(sleep), 10L), ] )))
Your (corrected) suggestion is the same as one of mine, and doesn't do what I'm looking for. -----Original Message----- From: David Winsemius [mailto:dwinsem...@comcast.net] Sent: Tuesday, 22 May 2012 3:37p To: Steve Taylor Cc: r-help@r-project.org Subject: Re: [R] glm(weights) and standard errors On May 21, 2012, at 10:58 PM, Steve Taylor wrote: > Is there a way to tell glm() that rows in the data represent a certain > number of observations other than one? Perhaps even fractional > values? > > Using the weights argument has no effect on the standard errors. > Compare the following; is there a way to get the first and last models > to produce the same results? > > data(sleep) > coef(summary(glm(extra ~ group, data=sleep))) coef(summary(glm(extra ~ > group, data=sleep, > weights=rep(10L,nrow(sleep))))) Here's a reasonably simple way to do it: coef(summary(glm(extra ~ group, data=sleep[ rep(10L,nrow(sleep)), ] ))) -- David. > sleep10 = sleep[rep(1:nrow(sleep),10),] coef(summary(glm(extra ~ > group, data=sleep10))) coef(summary(glm(extra ~ group, data=sleep10, > weights=rep(0.1,nrow(sleep10))))) > > My reason for asking is so that I can fit a model to a stacked > multiple imputation data set, as suggested by: > > Wood, A. M., White, I. R. and Royston, P. (2008), How should variable > selection be performed with multiply imputed data?. > Statist. Med., 27: 3227-3246. doi: 10.1002/sim.3177 > > Other suggestions would be most welcome. > ______________________________________________ R-help@r-project.org mailing list 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.
