# [R] Competing risks Kalbfleisch & Prentice method

Arthur Allignol arthur.allignol at fdm.uni-freiburg.de
Thu Mar 26 11:36:26 CET 2009

```I don't think there is a package to do that.

But you could have a look at ?predict.crr.

Best regards,
Arthur Allignol

Eleni Rapsomaniki wrote:
>
>
> Dear R users
>
>
>
> I would like to calculate the Cumulative incidence for an event
> adjusting for competing risks and adjusting for covariates. One way to
> do this in R is to use the cmprsk package, function crr. This uses the
> Fine & Gray regression model. However, a simpler and more classical
> approach would be to implement the Kalbfleisch & Prentice method (1980,
> p 169), where one fits cause specific cox models for the event of
> interest and each type of competing risk, and then calculates incidence
> based on the overall survival.  I believe that this is what the cuminc
> function in the aforementioned package does, but it does not allow to
> adjust for a vector of covariates.
>
>
>
> My question is, is there an R package that implements the Kalbfleisch &
> Prentice method for competing risks with covariates?
>
>
>
> for example, if k1 is the cause of interest among k competing causes:
>
> P_k1(t; x)=P(T<=t, cause=k1|x)=Sum(u=0, ..., u=t) {hazard_k(u;x)*S(u;x)}
>
> where S(u;x) = exp{-sum_of_k(sum(hazard_k(u))}
>
>
>
> I have searched extensively for an implementation of this in many
> packages, but it appears that more complex approaches are more commonly
> implemented, such as timereg package.
>
>
>
> Eleni Rapsomaniki
>
>
>
> Research Associate
>
> Strangeways Research Laboratory
>
> Department of Public Health and Primary Care
>
>
>
> University of Cambridge
>
>
>
>
>
>
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