Bayesian Model Averaging in Proportional Hazard Models: Assessing the Risk of a Stroke
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چکیده
منابع مشابه
Bayesian Model Averaging in Proportional Hazard Models: Assessing Stroke Risk
Evaluating the risk of stroke is important in reducing the incidence of this devastating disease. Here, we apply Bayesian model averaging to variable selection in Cox proportional hazard models in the context of the Cardiovascular Health Study, a comprehensive investigation into the risk factors for stroke. We introduce a technique based on the leaps and bounds algorithm which e ciently locates...
متن کاملBayesian Model Averaging in Proportional Hazard Models: Assessing the Risk of a Stroke
In the context of the Cardiovascular Health Study, a comprehensive investigation into the risk factors for stroke, 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 ...
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Cox’s proportional hazard (CPH) model is a statistical technique that captures the interaction between a set of risk factors and an effect variable. While the CPH model is popular in survival analysis, Bayesian networks offer an attractive alternative that is intuitive, general, theoretically sound, and avoids CPH model’s restrictive assumptions. Existing CPH models are a great source of existi...
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ژورنال
عنوان ژورنال: Journal of the Royal Statistical Society: Series C (Applied Statistics)
سال: 1997
ISSN: 0035-9254,1467-9876
DOI: 10.1111/1467-9876.00082