Hi Dr. Snow,
I am a graduate student working on analyzing data for my thesis and came across your post on an R forum: The default link function for the glm poisson family is a log link, which means that it is fitting the model: log(mu) ~ b0 + b1 * x But the data that you generate is based on a linear link. Therefore your glm analysis does not match with how the data was generated (and therefore should not necessarily be the best fit). Either analyze using glm and a linear link, or generate the data based on a log link (e.g. rpois(40, exp(seq(1,3, length.out=40))) ). Hope this helps, -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare greg.snow at imail.org <https://stat.ethz.ch/mailman/listinfo/r-help> 801.408.8111 I am not using R at the moment (working in SPSS, have to love the GUI) but my question is quite related: I am running a generalized linear model on data highly skewed to the right with a bunch of zeroes, so I decided to use the Tweedie distribution. In the model I ran both untransformed data (with link=log) as well as log(x+1) transformed data (with link=identity). The latter model had a much smaller (more negative) AICc value than the untransformed data with link=log. Is it valid to run the GLM with log(x+1) transformed data if link=identity? Or am I violating some kind of assumption about the model? I really appreciate any advice or thoughts! It seems as if my go-to statistician has taken a loooong break and any help would be greatly valued! -Emily Bellush q...@iup.edu Indiana University of Pennsylvania [[alternative HTML version deleted]] ______________________________________________ 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.
