# R/predict.GORMC.R In GORCure: Fit Generalized Odds Rate Mixture Cure Model with Interval Censored Data

#### Documented in predict.GORMC

```predict.GORMC <-
function(object,...){
arg<-list(...)
M<-length(object\$ParEst\$Eta)
P<-length(object\$ParEst\$Beta)

if(is.null(arg\$len)) arg\$len<-100
if(is.null(arg\$new.z)) arg\$new.z<-c(1,rep(0,M-1))
if(is.null(arg\$new.x)) arg\$new.x<-rep(0,P)
new.z<-as.vector(arg\$new.z)
new.x<-as.vector(arg\$new.x)
mdata<-object\$mdata
ti<-unique(c(0,na.omit(mdata\$Li),na.omit(mdata\$Ri)))
if(is.null(arg\$tp)){
tp<-seq(0,max(ti),length.out=arg\$len)
}else{
tp<-arg\$tp
}
pzi<-exp(sum(object\$ParEst\$Eta*new.z))/(1+exp(sum(object\$ParEst\$Eta*new.z)))
exb<-exp(sum(object\$ParEst\$Beta*new.x))
Het.est1<-t(Ispline(tp[tp<=max(ti)],order=object\$ParEst\$order,knots=object\$ParEst\$knots))%*%object\$ParEst\$gl
obj<-smooth.spline(tp[tp<=max(ti)],Het.est1)
Het.est2<-predict(obj,x=tp[tp>max(ti)],deriv=0)\$y

if(object\$ParEst\$r>0)  sut<-(1+object\$ParEst\$r*c(Het.est1,Het.est2)*exb)^(-1/object\$ParEst\$r)
if(object\$ParEst\$r==0)  sut<-exp(-c(Het.est1,Het.est2)*exb)

surv<-1-pzi+pzi*sut
pred<-list(CureRate=1-pzi,Survival=data.frame(Time=tp,SurvProb=surv))
class(pred)<-"GORMC"
class(pred)<-"predict.GORMC"
return(pred)
}
```

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GORCure documentation built on May 30, 2017, 2:59 a.m.