Gabor Grothendieck wrote: > On Wed, Apr 21, 2010 at 4:26 PM, Peter Dalgaard <pda...@gmail.com> wrote: ... >> I.e., that R reverts to using indicator variables when the intercept is >> absent. > > Is there any nice way of getting contr.sum coding for the interaction > as opposed to the ugly code in my post that I used to force it? i.e. > cbind(1, model.matrix(~ fac)[,2:3] * scores)
I think not. In general, an interaction like ~fac:scores indicates three lines with a common intercept and three different slopes, and changing the parametrization is not supposed to change the model, whereas your model inserts a restriction that the slopes sum to zero (if I understand correctly). So if you want to fit "ugly" models, you get to do a little ugly footwork. (A similar, simpler, issue arises if you want to have a 2x2 design with no effect in one column and/or one row (think clinical trial, placebo vs. active, baseline vs. treated. You can only do this us explicit dummy variables, not with the two classifications represented as factors.) -- Peter Dalgaard Center for Statistics, Copenhagen Business School Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
