[R] selectFGR - variable selection in fine gray model for competing risks

Thomas Alexander Gerds tag at biostat.ku.dk
Mon Mar 19 08:33:30 CET 2018

Dear Raja

the technical problem is that the function crrstep does not communicate
the selected variables in a proper way. the function pec::selectFGR uses
rownames(crrstep.fit$coefficients). the other problem is that I don't
like and never use backward elemination -- so, I am not motivated to fix
this. However, I copy this email to Rob van Kruijsdijk who wrote the
function ... maybe he wants to fix. you can always fix this yourself by
copying the functions selectFGR, predictEventProb.selectFGR.

Best Thomas

"Raja, Dr. Edwin Amalraj" <amalraj.raja at abdn.ac.uk> writes:

> Dear All,
>    I would like to use R function 'selectFGR' of fine gray model in
> competing risks model.  I used the 'Melanoma' data in 'riskRegression'
> package.  Some of the variables are factor.  I get solution for full
> model but not in variable selection model.  Any advice how to use
> factor variable in 'selectFGR' function.  The following R code is
> produced below for reproducibility.
> library(riskRegression)
> library(pec)
> dat <-data(Melanoma,package="riskRegression")
> Melanoma$logthick <- log(Melanoma$thick)
> f1 <- Hist(time,status)~age+sex+epicel+ulcer
> df1 <-FGR(f1,cause=1, data=Melanoma)
> df1
> df <-selectFGR(f1, data=Melanoma, rule ="BIC",  direction="backward")
> Thanks in advice for your suggestion. Is there any alternative solution ?
> Regards
> Amalraj raja
> The University of Aberdeen is a charity registered in Scotland, No SC013683.
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