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{MEDSTATS} competing risk model with time dependent covariates under R or Splus

Philippe,

The machinery to use is to split follow-up time so finely that you can safely assume that rates are constant in each interval, and then just stuff it all into a Poisson model. This allows you to use any kind of time-dependent variables as well as accommodating competing risks.

In the Epi package (http://staff.pubhealth.ku.dk/~bxc/Epi/) on CRAN there is a machinery for representation and manipulation of multistate data (of which competing risks are a special case), see the function Lexis().
It also has a time-splitting function there, splitLexis().

If you take a look at practical 14 from this year's SPE course:
http://staff.pubhealth.ku.dk/~bxc/SPE/2008/pracs.pdf
there is an example that addresses the problem you are having, practical no. 14.
If go to the folder
http://staff.pubhealth.ku.dk/~bxc/SPE/2008/R
you will find the R-code that runs the solution to the practical. The data used is a part of the Epi-package, so you just have to load the Epi package first.

It is however not using the Fine/Gray approach, but is directly modelling the cause-specific rates taking time dependent covariates into account.

Best regards,
Bendix
______________________________________________

Bendix Carstensen
Senior Statistician
Steno Diabetes Center
Niels Steensens Vej 2-4
DK-2820 Gentofte
Denmark
+45 44 43 87 38 (direct)
+45 30 75 87 38 (mobile)
bxc at steno.dk   http://www.biostat.ku.dk/~bxc
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