Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Bayesian Analysis for Heat Effects on Mortality

  • Jo, Young-In (Department of Statistics, Seoul National University) ;
  • Lim, Youn-Hee (Graduate School of Public Health, Seoul National University) ;
  • Kim, Ho (Graduate School of Public Health, Seoul National University) ;
  • Lee, Jae-Yong (Department of Statistics, Seoul National University)
  • Received : 2012.04.03
  • Accepted : 2012.08.13
  • Published : 2012.09.30
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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 $25^{\circ}C{\sim}29^{\circ}C$ and the mortality around the threshold changes from -1% to 2~13%.

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References

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