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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 제13권 제3호
- 발행연도
- 2011.1
- 수록면
- 1,101 - 1,109 (9page)
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초록· 키워드
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The Cox model has been widely used for the analysis of survival data under the proportional hazards assumption. The subject of examining the hazard proportionality assumption in survival data analysis has been studied extensively. One of methods for modeling nonproportional hazards is to use time-varying coefficient functions associated with covariates. In this paper, we propose a simple nonparametric method for estimating time- varying coefficient functions in hazard regression model via penalized likelihood by using a lower-dimensional approximation. Also, Bayesian confidence intervals are computed derived from Bayes model for the lower-dimensional approximations. The proposed method is illustrated by using a real data on patients diagnosed with AIDS in Australia.
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참고문헌 (22)
참고문헌 신청
Cox,D.R / 1972 / Regression models and life tables (with discussion) / Journal of the Royal Statistical Society, Series B 34 : 187 ~ 220
Du, P. / 2006 / Penalized likelihood hazard estimation: efficient approximation and bayesian confidence intervals / Statistics and Probability Letters 76 : 244 ~ 254
Gray,R.J / 1992 / Flexible methods for analyzing survival data using splines, with applications to breast cancer prognosis / Journal of American Statistical Association 87 :
Gu, C. / 2002 / Penalized likelihood regression: General formulation and efficient approximation / Canadian Journal of Statistics 30 (4) : 619 ~ 628
Gu,C / 2002 / Smoothing Spline ANOVA models / Springer-Verlag
Du, P. / 2006 / Penalized likelihood hazard estimation: efficient approximation and bayesian confidence intervals / Statistics and Probability Letters 76 : 244 ~ 254
Gray,R.J / 1992 / Flexible methods for analyzing survival data using splines, with applications to breast cancer prognosis / Journal of American Statistical Association 87 :
Gu, C. / 2002 / Penalized likelihood regression: General formulation and efficient approximation / Canadian Journal of Statistics 30 (4) : 619 ~ 628
Gu,C / 2002 / Smoothing Spline ANOVA models / Springer-Verlag
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