Competing risks analysis for discrete time-to-event data

This article presents an overview of statistical methods for the analysis of discrete failure times with competing events. We describe the most commonly used modeling approaches for this type of data, including discrete versions of the cause-specific hazards model and the subdistribution hazard model. In addition to discussing the characteristics of these methods, we present approaches to nonparametric estimation and model validation. Our literature review suggests that discrete competing-risks analysis has gained substantial interest in the research community and is used regularly in econometrics, biostatistics, and educational research.