[R] survival survfit with newdata

[Damjan Krstajic]

Thanks David for prompt reply. I agree with you. However, I still fail to get the survfit function to work with newdata. In my previous example I changed the column names of testX matrix and I still fail. 

> colnames(testX)<-names(coxph.model$coefficients)
> sfit<- survfit(coxph.model,newdata=data.frame(testX))
Error in model.frame.default(formula = Surv(trainTime, trainStatus) ~  :
  variable lengths differ (found for 'trainX')

What would be solution in my simple example to get the survival curves for testX? Thanks in advance. DK

> CC: r-help at r-project.org
> From: dwinsemius at comcast.net
> To: dkrstajic at hotmail.com
> Subject: Re: [R] survival survfit with newdata
> Date: Thu, 17 May 2012 00:52:55 -0400
> 
> 
> On May 16, 2012, at 5:08 PM, Damjan Krstajic wrote:
> 
> >
> > Dear all,
> >
> > I am confused with the behaviour of survfit with newdata option.
> 
> Yes. It has the same behavior as any other newdata/predict from  
> regression. You need to supply a dataframe with the same names as in  
> the original formula. Doesn't look as though that strategy is being  
> followed. The name of the column needs to be 'trainX' since that was  
> what was its name on the RHS of hte formula,  and you may want to  
> specify times. If you fail to follow those rules, the function falls  
> back on offering estimates from the original data.
> 
> >
> > I am using the latest version R-2-15-0. In the simple example below  
> > I am building a coxph model on 90 patients and trying to predict 10  
> > patients. Unfortunately the survival curve at the end is for 90  
> > patients.
> 
> As is proper with a malformed newdata argument.
> 
> > Could somebody please from the survival package confirm that this  
> > behaviour is as expected or not - because I cannot find a way of  
> > using 'newdata' with really new data. Thanks in advance. DK
> >
> >> x<-matrix(rnorm(100*20),100,20)
> >
> >>
> > time<-runif(100,min=0,max=7)
> >
> >>
> > status<-sample(c(0,1), 100, replace = TRUE)
> >> trainX<-x[11:100,]
> >>
> > trainTime<-time[11:100]
> >>
> > trainStatus<-status[11:100]
> >>
> > testX<-x[1:10,]
> >> coxph.model<-
> > coxph(Surv(trainTime,trainStatus)~ trainX)
> >> sfit<- survfit(coxph.model,newdata=data.frame(testX))
> >
> >>
> > dim(sfit$surv)
> >
> > [1] 90 90
> >
> >
> > 		 	   		
> > 	[[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> 
> David Winsemius, MD
> West Hartford, CT
>