Terry Therneau <thern...@mayo.edu> writes:
> --begin inclusion --
> I have a matched-case control dataset that I'm using conditional
> logistic regression (clogit in survival) to analyze. I'm trying to
> conduct k-folds cross validation on my top models but all of the
> packages I can find (CVbinary in DAAG, KVX) won't work with clogit
> models. Is there any easy way to do this in R?
> -end inclusion --
>
> The clogit funciton is simply a wrapper for coxph.
> clogit(case ~ ...
> turns into
> coxph(Surv(dummy, case) ~ ...
> where "dummy" is a vector of ones.
>
> Do the packages support coxph models?
Terry,
I do not know the answer to the question you posed, but I suspect the
answer is no.
The cross-validation would need to be done stratum-wise, but that does
not seem to be supported by predict.coxph():
> fit <- clogit(case~spontaneous+induced+strata(stratum),data=infert)
> train.sans.1 <- update(fit,subset=stratum!=1)
> predict.1 <- predict(train.sans.1,newdat=subset(infert,stratum==1))
Error in predict.coxph(train.sans.1, newdat = subset(infert, stratum == :
New data has a strata not found in the original model
One can work around this:
> train.sans.1.alt <- update(fit,subset= stratum!=1 | case == 1 )
> all(coef(train.sans.1),coef(train.sans.1.alt))
[1] TRUE
> predict.1.alt <- predict(train.sans.1.alt,newdat=subset(infert,stratum==1))
but the predicted values are not centered in each stratum as usual with
strata in predict.coxph (if that matters):
> predict.1.alt
1 84 166
0.000000 -2.527759 -2.527759
> predict.1.alt - mean(predict.1.alt)
1 84 166
1.6851724 -0.8425862 -0.8425862
Best,
Chuck
>
> Terry T
>
--
Charles C. Berry Dept of Family/Preventive Medicine
ccberry at ucsd dot edu UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901
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