Leo Vorthoren <L.Vorthoren <at> nioo.knaw.nl> writes: > I have been using generalized linear models in SPSS 18, in order to build > models and to calculate the P values. When I was building models in Excel > (using the intercept and Bs from SPSS), I noticed that the graphs differed > from my expectations. When I ran the dataset again in R, I got totally > different outcomes for both the P values as well as the Bs and the > intercepts. The outcomes of R seem much more likely to be the correct ones, > but I really cannot explain the differences.
I appreciate/assume that you're asking on the off chance that someone else has tried something very similar and gone to the trouble of figuring out the differences between R's and SPSS's default setup, but you're unlikely to get an answer without more detailed information. My best guess is that SPSS and R are using different contrasts and/or different baseline levels. R uses treatment contrasts by default, and assumes that the first (alphabetical) level of a factor is the baseline level. It's conceivable that you have a dataset where the results are numerically unstable and sensitive to small details in the algorithms used. ______________________________________________ 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.
