Bayesian Analysis for Heat Effects on Mortality

Title & Authors
Bayesian Analysis for Heat Effects on Mortality
Jo, Young-In; Lim, Youn-Hee; Kim, Ho; Lee, Jae-Yong;

Abstract
In this paper, we introduce a hierarchical Bayesian model to simultaneously estimate the thresholds of each 6 cities. It was noted in the literature there was a dramatic increases in the number of deaths if the mean temperature passes a certain value (that we call a threshold). We estimate the difference of mortality before and after the threshold. For the hierarchical Bayesian analysis, some proper prior distribution of parameters and hyper-parameters are assumed. By combining the Gibbs and Metropolis-Hastings algorithm, we constructed a Markov chain Monte Carlo algorithm and the posterior inference was based on the posterior sample. The analysis shows that the estimates of the threshold are located at $\small{25^{\circ}C{\sim}29^{\circ}C}$ and the mortality around the threshold changes from -1% to 2~13%.
Keywords
Hierarchical Bayesian model;threshold;Markov chain Monte Carlo algorithm;
Language
Korean
Cited by
1.
카드뮴 반응용량 곡선에서의 기준용량 평가를 위한 베이지안 분석연구,이민제;최태련;김정선;우해동;

응용통계연구, 2013. vol.26. 3, pp.453-470
1.
Bayesian Analysis of Dose-Effect Relationship of Cadmium for Benchmark Dose Evaluation, Korean Journal of Applied Statistics, 2013, 26, 3, 453
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