Bayesian Competing Risks 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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- 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
- Crowder, M. J. (2001). Classical Competing Risks. Chapman and Hall/CRC. · ISBN 9781584881759
Curated claims
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Related methods
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