Competing risks/events

[onacrame]

If I have competing events and I treat the occurrence of a competing events as censored observations (informative/dependent censoring) will this model still give me an unbiased estimate of survival? In my use case the competing event will be one that precludes the event of interest, so the two events are completely mutually exclusive, I'm interested in event A, but if event B happens, then event A can never happen.

Generally I gather that competing events can work within a Cox framework, but it will give a biased estimate of incidence using a Kaplan Meier approach and XGBSE partially relies on Kaplan Meier.

[GabrielGimenez]

Given the informative censoring XGBSEKaplanNeighbors and XGBSEKaplanTree modules would return biased estimatives, but XGBSEDebiasedBCE should work just fine!

[onacrame]

Great thanks!

[GabrielGimenez]

@onacrame I'm not sure the survival curve will be meaningful tho, you might have to use return_interval_probs=True on predict and interpret your interval probabilities.

Actually, I don't know what would happen in your use case and since the XGBSEDebiasedBCE approximate a kaplan meier it might still return biased estimations

[onacrame]

Noted thanks.