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Updated: May 7, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A discrete-time Multiple Event Process Survival Mixture (MEPSUM) model
Danielle O Dean1, Daniel J Bauer1, Michael J Shanahan2
1Department of Psychology, University of North Carolina.
Abstract:
Traditional survival analysis was developed to investigate the occurrence and timing of a single event, but researchers have recently begun to ask questions about the order and timing of multiple events. A multiple event process survival mixture model is developed here to analyze nonrepeatable events measured in discrete-time that may occur at the same point in time. Building on both traditional univariate survival analysis and univariate survival mixture analysis, the model approximates the underlying multivariate distribution of hazard functions via a discrete-point finite mixture in which the mixing components represent prototypical patterns of event occurrence. The model is applied in an empirical analysis concerning transitions to adulthood, where the events under study include parenthood, marriage, beginning full-time work, and obtaining a college degree. Promising opportunities, as well as possible limitations of the model and future directions for research, are discussed.
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