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question about GLM
2 messages · Aiste Aistike, Ben Bolker
Aiste Aistike <aiste.aistike <at> gmail.com> writes:
Hello R-users, I do not have much knowledge about generalized linear models therefore my question maybe quite stupid. I have data from 20 towns with their population and number of people with an illness from those towns. I would like to use glm function in R so I can calculate proportions of ill people (and later on produce confidence intervals). I also want to compare those with original proportions of ill people. If I use: model1 <- glm(ill ~ offset(log(total)), family = poisson) # ill - number of people with illness #total - total number of people with predict.glm I could get number of people (count data), but not the proportions. If the obtained number I divide by 'total', I get the same proportion for everyone. But what I want is a way of modeling proportions. This probably requires to fit a different model but my lack of knowledge isn't helping here.
Not stupid -- but -- wouldn't a binomial model glm(cbind(ill,total-ill) ~ 1, family=binomial) make more sense? Read ?predict.glm carefully to determine whether you are predicting responses on the linear predictor (=log-odds) scale or the original scale Ben Bolker