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2009 Jun 23
0
Fractional Polynomials in Competing Risks setting
...ich transformation, if any, is best. This was possible as the Cox model was the underlying model. However, I am now at the situation where the assumption that the competing risks are independent is no longer true and therefore I cannot use the Cox model. The code I used to get the MFP model was: coxfitf <- mfp(Surv(with.Withtime,with.Wcens)~fp(all.age),family=cox,data=nearma,select=0.05,verbose=TRUE) where with.Withtime is the time to treatment withdrawal, with.Wcens is the censoring indictor for the event and all.firstint is the age at baseline. To look at the competing risks regression model...