# Cox proportional hazards with multiclass dependent variable

Is it possible to perform a multiclass Cox proportional hazards model? I'm interested in finding the probability of self cure on consumer loans, or just study how self-curing clients behave so as to identify future customers that behave the same way. My dependent variable of interest has 3 classes: -not cured (0) -cured after being contacted (1) -self cured (2)

I was thinking maybe two regressions have to be run in this case (similarly as in the multinomial logit), one where it's 0 vs 1, and another where it is 0 vs 2, maybe another 1 vs 2?

I tried looking for this but I didn't find anything, so I'm wondering if it's possible at all?

This seems to be a fairly straightforward "competing risks" analysis. If "cured" is your event, then you simply code the event differently depending on whether it was a "self-cure" or "cure-after-being-contacted". In general, instead of a coding {0,1} for {censored, event} you code {0,1,2,...} for {censored, eventType1, eventType2, ...}. That's handled pretty simply in the R survival package, for example. See Section 2.3 of the main survival vignette of that package.
• @amestrian multi-state models with arbitrary transition patterns and competing risks are possible to model this way. See the multi-state vignette for the survival package. Of course it gets more complicated the more transitions that you allow, and data formatting might get dicey. I don't have any substantive experience with such models, but now you know the buzz-words for which to search. – EdM Aug 28 at 18:01