On 5/22/2009 9:58 AM, Laura Bonnett wrote:> Dear All,
>
> I am attempting to use forward and/or backward selection to determine
> the best model for the variables I have. Unfortunately, because I am
> dealing with patients and every patient is receiving treatment I need
> to force the variable for treatment into the model. Is there a way to
> do this using R? (Additionally, the model is stratified by
> randomisation period). I know that SAS can be used to do this but my
> SAS coding is poor and consequently it would be easier for me to use
> R, especially given the fractional polynomial transformations!
>
> Currently the model is as follows (without treatment).
>
>
coxfita=coxph(Surv(rem.Remtime,rem.Rcens)~sind(nearma)+fsh(nearma)+fdr(nearma)+th1(nearma)+th2(nearma)+fp(cage)+fp(fint)+fp(tsb)+strata(rpa),data=nearma)
>
>
> Thank you for your help,
>
> Laura
See the scope argument to stepAIC in the MASS package. You can
specify a formula in the 'lower' component of scope which includes the
treatment variable. That will force the treatment variable to remain in
every model examined in the stepwise search.
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--
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