[R] less than full rank contrast methods
mxkuhn at gmail.com
Tue Dec 7 11:19:07 CET 2010
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)
On Dec 6, 2010, at 10:29 PM, Frank Harrell <f.harrell at 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 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
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