Gustaf Granath wrote: > Hi all, > > I hope this question is not too trivial. I can't find an explanation > anywhere (Stats and R books, R-archives) so now I have to turn to the R-list. > > Question: > > If you have a factorial design with two factors (say A and B with two > levels each). What does the intercept coefficient with > treatment.contrasts represent?? > > Here is an example without interaction where A has two levels A1 and > A2, and B has two levels B1 and B2. So R takes as a baseline A1 and B1. > > coef( summary ( lm ( fruit ~ A + B, data = test))) > > Estimate Std. Error t value Pr(>|t|) > (Intercept) 2.716667 0.5484828 4.953058 7.879890e-04 > A2 6.266667 0.6333333 9.894737 3.907437e-06 > B2 5.166667 0.6333333 8.157895 1.892846e-05 > > I understand that the mean of A2 is +6.3 more than A1, and > that B2 is 5.2 more than B1. > > So the question is: Is the intercept A1 and B1 combined as one mean > ("the baseline")? or is it something else? Does this number actually > tell me anything > useful (2.716)?? > > What does the model (y = intercept + ??) look like then? I can't understand > how both factors (A and B) can have the same intercept? > > Consider an AxB crosstable of (fitted) means. Upper left corner is intercept , add A2, B2, or both to get the other three cells.
-- O__ ---- Peter Dalgaard Ă˜ster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ 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.