Process / pipelineClinical / epidemiology

Bayesian Competing Risks Analysis — Bayesian Competing Risks Survival Analysis

Bayesian competing risks analysis is a time-to-event method for settings where subjects can fail from more than one mutually exclusive cause — such as death from cancer versus death from cardiovascular disease — and prior knowledge or small-sample uncertainty makes a Bayesian framework advantageous. It extends classical competing risks models (cause-specific hazards and cumulative incidence functions) by placing probability distributions over unknown parameters and updating those distributions with observed data, yielding full posterior inference for each failure type.

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Sources

  1. Larson, M. G., & Dinse, G. E. (1985). A mixture model for the regression analysis of competing risks data. Applied Statistics, 34(3), 201–211. DOI: 10.2307/2347464
  2. Crowder, M. J. (2001). Classical Competing Risks. Chapman and Hall/CRC. ISBN: 9781584881759

Related methods

ScholarGateBayesian Competing Risks Analysis (Bayesian Competing Risks Survival Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/epidemiology/bayesian-competing-risks-analysis