응용통계연구 (The Korean Journal of Applied Statistics)

  • 제18권1호
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  • Pages.67-81
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  • 2005
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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동측치가 많은 FRAILTY 모형의 분석

Analysis of the Frailty Model with Many Ties

  • 김용대 (서울대학교 통계학과) ;
  • 박진경 (서울대 연구공원 내, 국제백신연구소(IVI))
  • Kim Yongdai (Dept. of Statistics, Seoul National University) ;
  • Park Jin-Kyung (Associate Scientfic Analyst, International Vaccine Institute, SNU Research Park)
  • 발행 : 2005.03.01
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⟨ 이전 논문 다음 논문 ⟩

초록

프레일티모형에 대한 기존의 추론방법은 동측치가 많은 경우에 그 성능이 떨어진다. 그 이유는 사용된 경험적 우도함수가 동측치가 많은 자료에는 적합하지 않기 때문이다. 본 논문에서는 동측치가 많은 프레일티 모형에서의 새로운 추론방법을 제안한다. 이항형태의 경험적우도함수를 바탕으로 베이지안 부스트랩을 사용하여 모수의 사후분포를 구한다. 제안된 방법의 장점은 기존에 제안된 주변최대우도추정량에 비하여 계산이 수월하고 안정적인 결과를 제공하는데 있다. 이를 실증적으로 비교하기 위하여 제안된 방법을 주변최대우도추정량과 가상실험을 통하여 비교한다.

Most of the previously proposed methods for the frailty model do not work well when there are many tied observations. This is partly because the empirical likelihood used is not suitable for tied observations. In this paper, we propose a new method for the frailty model with many ties. The proposed method obtains the posterior distribution of the parameters using the binomial form empirical likelihood and Bayesian bootstrap. The proposed method yields stable results and is computationally fast. To compare the proposed method with the maximum marginal likelihood approach, we do simulations.

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