Bayesian Model Averaging in Proportional Hazard Models: Assessing the Risk of a Stroke
Abstract
SUMMARY: In the context of the Cardiovascular Health Study, a comprehensive investigation into the risk factors for strokes, we apply Bayesian model averaging to the selection of variables in Cox proportional hazard models. We use an extension of the leaps-and-bounds algorithm for locating the models that are to be averaged over and make available S-PLUS software to implement the methods. Bayesian model averaging provides a posterior probability that each variable belongs in the model, a more directly interpretable measure of variable importance than a P-value. P-values from models preferred by stepwise methods tend to overstate the evidence for the predictive value of a variable and do not account for model uncertainty. We introduce the partial predictive score to evaluate predictive performance. For the Cardiovascular Health Study, Bayesian model averaging predictively outperforms standard model selection and does a better job of assessing who is at high risk for a stroke.
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“Draper (1995), Raftery, Madigan and Volinsky (1996) and Volinsky et al. (1997) show its usefulness in the BMA context.”
From Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and E. I. George, and a rejoinder by the authors (1999) · cites this paper as Volinsky et al. (1997)
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- Authors
- Volinsky, C. T., Madigan, D., Raftery, A. E., & Kronmal, R. A.
- Affiliations
- University of Washington (US)
- Corresponding author
- Volinsky, Chris T.
- Venue
- Journal of the Royal Statistical Society Series C: Applied Statistics
- Publisher
- Oxford University Press (OUP)
- Published
- 1997-12-01
- Volume
- 46
- Issue
- 4
- Pages
- 433-448
- ISSN
- 0035-9254 (ISSN-L)
- 1467-9876
- OpenAlex
- W2083927895
- Cited by
- 226
- References
- 7
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 3 · 2023: 1 · 2022: 7 · 2021: 7 · 2020: 5 · 2019: 6 · 2018: 9 · 2017: 8 · 2016: 13 · 2015: 14 · 2014: 14 · 2013: 15 · 2012: 10
- FWCI
- 2.34
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Journal of the Royal Statistical Society Series C (Applied Statistics) (publishedVersion)
- Funders
- National Science Foundation
- Office of Naval Research (N00014)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- Bayesian model averaging, Cox proportional hazards model, stroke risk factors, Cardiovascular Health Study, feature selection, model uncertainty, feature importance
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