I have a data in which I have to apply a competing risk. 4 variables:

  • Temps_Competing_Descompensacio: the time to event.
  • Competing_Descompensacio: factor variable to identifie the event, censored, event or competing event.
  • Grup_IQ: stratified analisis (2 groups).
  • IPTW: the weights of the observation from a previous propensity score phase.

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My problem is to apply a method for competing risks with the propensity score IPTW weights.

I haven't found a way to do it. The analysis without the weights was correct. Already tested and compared with a SAS sintax. Here my code from the for the crr function from the cmprsk package

fit.crr <- crr(ftime = Competing_dataset$Temps_Competing_Descompensacio, 
               fstatus = Competing_dataset$Competing_Descompensacio,
               cov1 = Competing_dataset$Grup_IQ, failcode = 1, cencode = 0)

The issue comes when I try to add the weights, as I do not see or find an argument to ponderate the results. I considered multiplying the time variables for the weights, but does not seem correct from methodolgy perspective, and I haven't found a solution from other libraries.