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Hierarchical Bayes Analysis of Smoking and Lung Cancer Data
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 Title & Authors
Hierarchical Bayes Analysis of Smoking and Lung Cancer Data
Oh, Man-Suk; Park, Hyun-Jin;
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 Abstract
Hierarchical models are widely used for inference on correlated parameters as a compromise between underfitting and overfilling problems. In this paper, we take a Bayesian approach to analyzing hierarchical models and suggest a Markov chain Monte Carlo methods to get around computational difficulties in Bayesian analysis of the hierarchical models. We apply the method to a real data on smoking and lung cancer which are collected from cities in China.
 Keywords
Hierarchical model;Correlated parameters;Markov chain Monte Carlo;Meta analysis;
 Language
English
 Cited by
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