Risk factors of coronary heart disease: a Bayesian model averaging approach

Wang, DL; Lertsithichai, P; Nanchahal, K; Yousufuddin, M; (2003) Risk factors of coronary heart disease: a Bayesian model averaging approach. Journal of applied statistics, 30 (7). pp. 813-826. ISSN 0266-4763 DOI: https://doi.org/10.1080/0266476032000076074

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To analyse the risk factors of coronary heart disease (CHD), we apply the Bayesian model averaging approach that formalizes the model selection process and deals with model uncertainty in a discrete-time survival model to the data from the Framingham Heart Study. We also use the Alternating Conditional Expectation algorithm to transform the risk factors, such that their relationships with CHD are best described, overcoming the problem of coding such variables subjectively. For the Framingham Study, the Bayesian model averaging approach, which makes inferences about the effects of covariates on CHD based on an average of the posterior distributions of the set of identified models, outperforms the stepwise method in predictive performance. We also show that age, cholesterol, and smoking are nonlinearly associated with the occurrence of CHD and that P-values from models selected from stepwise methods tend to overestimate the evidence for the predictive value of a risk factor and ignore model uncertainty.

Item Type: Article
Keywords: artery-disease, regression, selection, mortality, events
Faculty and Department: Faculty of Public Health and Policy > Dept of Social and Environmental Health Research
Faculty of Epidemiology and Population Health > Dept of Medical Statistics
Web of Science ID: 184045400007
URI: http://researchonline.lshtm.ac.uk/id/eprint/16121


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