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2011 Sep 05
1
SAS code in R
...btain the survival estimates (at 1 year) and confidence intervals for combinations of risk factors for my outcome. /* Combinations of Risk Factors */ data test2; input sex treat; DATALINES; 0 0 1 0 0 1 1 1 ; run; /* Survival estimates for the above combinations */ proc phreg data = pudat2; model withtime*wcens(0) = sex treat /ties = efron; baseline out = surv2 survival = survival lower = slower upper = supper covariates = test2 /method = ch nomean cltype=loglog; run; /* Survival estimates at 1 year */ proc print data = surv2 noobs; where withtime = 364; run; I now would like to do the sam...
2009 Jun 23
0
Fractional Polynomials in Competing Risks setting
...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 modelling when age in untransform...
2009 Jun 25
2
crr - computationally singular
...em. The code I am using is as follows where covaea and covaeb are matrices of covarites, all coded as binary variables. In case a: > covaea <- cbind(sexa,fsha,fdra,nsigna,eega,th1a,th2a,stype1a,stype2a,stype3a,pgu1a,pgu2a,log(agea),firstinta/1000,totsezbasea) > fita <- crr(snearma$with.Withtime,csaea,covaea,failcode=2,cencode=0) and in case b: > covaeb <- cbind(sexb,fshb,fdrb,nsignb,eegb,th1b,th2b,stype1b,stype2b,stype3b,stype4b,stype5b,pgu1b,pgu2b,(ageb/10)^(-1),firstintb,log(totsezbaseb)) > fitb <- crr(snearmb$with.Withtime,csaeb,covaeb,failcode=2,cencode=0) csaea and csa...