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

Ronald Geskus statistics at inter.nl.net
Wed Mar 21 05:00:42 CET 2018

Dear Raja,

A Fine and Gray model can be fitted using the standard coxph function with
weights that correct for right censoring and left truncation. Hence I
guess any function that allows to perform stepwise regression with coxph
should work. See e.g. my article in Biometrics
https://doi.org/10.1111/j.1541-0420.2010.01420.x, or the vignette
"Multi-state models and competing risks" in the survival package.

best regards,

Ronald Geskus, PhD
head of biostatistics group
Oxford University Clinical Research unit
Ho Chi Minh city, Vietnam
associate professor University of Oxford

"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
> Tha Oilthigh Obar Dheathain na charthannas clàraichte ann an Alba, Àir.

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