I am trying to fit a large Cox model with many predictors. Because
there are many predictors, I would like to use the ridge() function to
get penalized ml estimates for all coefficients. The problems are that:
1. When I include a factor (like race) in the ridge() function, dummy
variables are not created. The resulting model has a single
coefficient for the race variable, and I have no idea what is the
interpretation of this coefficient. Obviously, I can create the dummy
variables myself, but it would be better not to.
2. When I include a large number of predictors in ridge() [> ~ 35],
coxph does not complete and I get the error: Error in
model.matrix.default(Terms, m) :
model frame and formula mismatch in model.matrix()
Using a smaller subset of the same covariates, I don't get this error
and it doesn't seem to matter which subset of covariates I use.
Any help with these problems would be greatly appreciated!
Thanks,
Jessica Myers
Instructor in Medicine
Division of Pharmacoepidemiology
Brigham and Women's Hospital
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