François Collin <stxfc <at> nottingham.ac.uk> writes: > > Dear all, > I would like to run a linear model which includes two factors:
> - The first one has two levels, including a reference level. Thus I > have to use the treatment contrast (contr.treatment, reference level > effect = 0, then the intercept). > - The second is a 6-level factor without reference contrast nor > order. So, I would like to use sum contrat: sum of the effects = 0. > The problem arises when it comes to the coefficient test. I > understand it is not relevant to test the reference level for the > first factor as the reference level is set to 0. However, using sum > contrast for the second factor, I would have expected the test of > each level to be included in the classical summary print of the lm > function result but it is not. And here is my problem, how can I > have every coefficients tested and printed in the summary output > when my factor is studied from this sum.contrast standpoint? [some context snipped to make gmane happy -- sorry ] I think you should look at the effects package or the lsmeans package (or possibly the multcomp package, if you want to be careful about the number of (non-orthogonal) tests) -- the issue is that summary.lm always reports on the *parameters* estimated. If some parameters are not independently estimable (e.g. the effect corresponding to the last level can be reconstructed from the parameter values for all of the preceding levels), then summary.lm() won't give them to you. In fact, these packages will (probably) give you the results you want even if the original model uses default treatment contrasts. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.