Hello everyone, I am currently teaching an intermediate stats. course at UCSD Extension using R. We are using Venables and Ripley as the primary text for the course, with Freund & Wilson's Statistical Methods as a secondary reference. I recently gave a homework assignment on logistic regression, and I had a question about glm. Let n be the number of trials, p be the estimated sample proportion, and w be the standard binomial weights n*p*(1-p). If you perform output <- glm(p ~ x, family = binomial, weights = n) you get a different result than if you perform the logit transformation manually on p and perform output <- lm(logit(p) ~ x, weights = w), where logit(p) is either obtained from R with qlogis(p) or from a manual computation of ln(p/1-p).
The difference seems to me to be too large to be roundoff error. The only thing I can guess is that the application of the weights in glm is different than in a manual computation. Can anyone explain the difference in results? Daniel Pick Principal Daniel Pick Scientific Software Consulting San Diego, CA E-Mail: [EMAIL PROTECTED] ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
