In medical research, how can we accurately analyze time-to-event data when multiple events can occur? This paper explores the competing risks model as a special case of a multi-state model. The research reviews the properties of the model, contrasting them with the latent failure time approach, and discusses the relationship between the competing risks model and right-censoring. It also provides a brief review of regression analysis of the cumulative incidence function. Through real data examples and a practical guide, the authors aim to equip practitioners with a better understanding of this approach. The study examines competing risks models and their properties, relation to right-censoring, and regression analysis. This model contributes to advanced methodologies for statistical analysis in medical research.
Published in Statistical Methods in Medical Research, this paper directly addresses the journal's focus on statistical approaches applied to medical studies. By examining the competing risks model, it offers a valuable tool for researchers analyzing time-to-event data in a medical context, furthering the journal's mission of advancing statistical applications in healthcare.