The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Bayesian Analysis of Dose-Effect Relationship of Cadmium for Benchmark Dose Evaluation

카드뮴 반응용량 곡선에서의 기준용량 평가를 위한 베이지안 분석연구

  • Lee, Minjea (Department of Statistics, Korea University) ;
  • Choi, Taeryon (Department of Statistics, Korea University) ;
  • Kim, Jeongseon (Molecular Epidemiology Branch, National Cancer Center) ;
  • Woo, Hae Dong (Molecular Epidemiology Branch, National Cancer Center)
  • 이민제 (고려대학교 통계학과) ;
  • 최태련 (고려대학교 통계학과) ;
  • 김정선 (국립암센터 분자역학연구과) ;
  • 우해동 (국립암센터 분자역학연구과)
  • Received : 2013.03.29
  • Accepted : 2013.05.21
  • Published : 2013.06.30
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Abstract

In this paper, we consider a Bayesian analysis of the dose-effect relationship of cadmium to evaluate a benchmark dose(BMD). For this purpose, two dose-response curves commonly used in the toxicity study are fitted based on Bayesian methods to the data collected from the scientific literature on cadmium toxicity. Specifically, Bayesian meta-analysis and hierarchical modeling build an overall dose-effect relationship that use a piecewise linear model and Hill model, where the inter-study heterogeneity and inter-individual variability of dose and effect such as gender, age and ethnicity are accounted. Estimation of the unknown parameters is made by using a Markov chain Monte Carlo algorithm based user-friendly software WinBUGS. Benchmark dose estimates are evaluated for various cut-offs and compared with different tested subpopulations with with gender, age and ethnicity based on these two Bayesian hierarchical models.

본 논문에서는 카드뮴의 반응-용량 모형에 대한 베이지안 분석을 실시하고 기준용량에 대한 추정값들을 유도하고 비교한다. 이를 위하여 독성물질에 대한 용량반응곡선에서 많이 활용되는 두 가지 모형을 사용하고, 카드뮴의 독성연구에 관련한 기존의 문헌으로 수집된 자료에 대한 성별, 연령, 인종, study code 등과 같은 소집단 간의 개별적 형질을 반영할 수 있는 베이지안 메타분석 관점에서의 모형분석을 실시한다. 이러한 두 가지 모형에 대한 베이지안 분석을 위하여 WinBUGS를 이용한 마르코프 연쇄 몬테칼로(Markov chain Monte Carlo; MCMC) 방법을 통하여 모수를 추정하고 이에 따른 다양한 기준용량들을 계산하고 비교해보았다. 베이지안 모형 적합뿐만 아니라 편차정보기준을 통해서 주어진 자료를 더 잘 설명하는 모형을 선택하는 베이지안 모형 선택을 고려하였고, 이를 실제 자료에 적용해본다.

Keywords

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