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Statistical Analysis of Recidivism Data Using Frailty Effect

프레일티를 이용한 재범 자료의 연구

  • Kim, Yang-Jin (Department of Statistics, Sookmyung Women's University)
  • 김양진 (숙명여자대학교 통계학과)
  • Received : 20100400
  • Accepted : 20100700
  • Published : 2010.08.31

Abstract

Recurrent event data occurs when a subject experience the event of interest several times and has been found in biomedical studies, sociology and engineering. Several diverse approaches have been applied to analyze the recurrent events (Cook and Lawless, 2007). In this study, we analyzed the YTOP(Young Traffic Offenders Program) dataset which consists of 192 drivers with conviction dates by speeding violation and traffic rule violation. We consider a subject-specific effect, frailty, to reflect the individual's driving behavior and extend to time-varying frailty effect. Another feature of this study is about the redefinition of risk set. During the study, subject may be under suspension and this period is regarded as non-risk period. Thus the risk variables are reformatted according to suspension and termination time.

재발 사건 자료(recurrent event data)는 연구 대상이 같은 종류의 사건을 여러 번 경험할 때 발생되는 자료 형태이다. 재발 사건간에 연관관계를 위해 프레일티가 사용된다. 프레일티 효과는 랜덤효과의 한 형태로 개인별 특성을 표현하기 위해 생존 분석에서 널리 적용되어 왔다. 본 논문에서는 이러한 개인별 효과가 시간에 따라 변할 수 있음을 가정하여 시간 가변 프레일티를 적용한다. 본 논문에서는 적용 사례로 범죄 재범 자료를 분석한다. 특히 일부 관측 대상들은 일정 기간 동안 연구에서 제외되는 불연속성을 경험하게 되며 이는 위험그룹(risk group)의 새로운 정의가 필요하다. 모수 추정을 위해 조각 상수 위험 함수가 사용되며 EM 알고리즘이 적용된다.

Keywords

References

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