Proportional subdistribution hazards regression for left-truncated competing risks data

Abstract

Fine and Gray [(1999), ‘A Proportional Hazards Model for the Subdistribution of a Competing Risk’, Journal of the American Statistical Association, 94, 496–509] considered a proportional subdistribution hazards model under the framework of competing risks. Using the partial likelihood principle and weighting techniques, they derived estimation and inference procedures for regression parameters under right censoring. In this article, we show that the partial likelihood approach to estimation is applicable when both right censoring and left truncation are present. We derive large sample properties of the proposed estimators and investigate their finite sample performances via simulation.

Keywords:

• hazard of subdistribution
• martingale
• partial likelihood