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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제9권 제2호
- 발행연도
- 2007.1
- 수록면
- 523 - 534 (12page)
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초록· 키워드
오류제보하기
Competing risks problems are often found in various applications such as clinical trials, epidemiological studies, reliability problems, and econometrics where multiple failure causes are simultaneously competing for the ultimate failure and incomplete observations are obtained. Moeschberger and Klein(1995) provided a survey of dependent competing risks problem via a thorough review of statistical literature. The purpose of this paper is to update Moeschberger and Klein(1995)'s review with statistical methods recently developed for competing risks problems without the independence assumption.
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참고문헌 (26)
참고문헌 신청
Anderson, P. / 2003 / Generalized linear models for correlated pseudo-observations, with applications to multi-state models / Biometrika 90 : 15 ~ 27
Bandeen-Roche, A. / 2002 / Modelling multivariate failure time associations in the presence of a competing risk / Biometrika 89 : 299 ~ 314
Braekers, R. / 2005 / Cox's regression model under partially informative censoring / Communications in Statistics 34 : 1793 ~ 1811
Bryand, J. / 2004 / Semiparametric Models for Cumulative Incidence Functions / Biometrics 60 : 182 ~ 190
Clayton, D. G. / 1978 / A model for association in bivariate life-tables and its application in epidemiological studies of familial tendency in chronic disease incidence / Bi
Bandeen-Roche, A. / 2002 / Modelling multivariate failure time associations in the presence of a competing risk / Biometrika 89 : 299 ~ 314
Braekers, R. / 2005 / Cox's regression model under partially informative censoring / Communications in Statistics 34 : 1793 ~ 1811
Bryand, J. / 2004 / Semiparametric Models for Cumulative Incidence Functions / Biometrics 60 : 182 ~ 190
Clayton, D. G. / 1978 / A model for association in bivariate life-tables and its application in epidemiological studies of familial tendency in chronic disease incidence / Bi
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