Greg and Frank, Thanks for the replies. I didn't express myself very well; I'm not interest in the model fitting aspect. I'd just like to get the full set of dummy variables (optimally from model.matrix)
Max On Dec 6, 2010, at 10:29 PM, Frank Harrell <f.harr...@vanderbilt.edu> wrote: > > Given a non-singular fit, the contrast function in the rms package will allow > you to request multi-dimensional contrasts some of which are redundant. > These singular contrasts are automatically ignored. One use for this is to > test for differences in longitudinal trends between two of three treatment > groups, where the time trend is a multiple degree of freedom > parameterization such as cubic splines. You don't have to stop and think > about how many time points to test; just test as many as you'd like and get > the right degrees of freedom according to the number of spline terms (main > effects + interactions). > > Frank > > ----- > Frank Harrell > Department of Biostatistics, Vanderbilt University > -- > View this message in context: > http://r.789695.n4.nabble.com/less-than-full-rank-contrast-methods-tp3074688p3075771.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > 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. ______________________________________________ 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.
