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Analyzing Left-truncated and Right-censored Data under Cox Models with Long-term Survivors
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作者 Fei-peng ZHANG YONG ZHOU 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2013年第2期241-252,共12页
We analyze left-truncated and right-censored data using Cox proportional hazard models with long-term survivors. The estimators of covariate coefficients and the long-term survivor proportion are obtained by the parti... We analyze left-truncated and right-censored data using Cox proportional hazard models with long-term survivors. The estimators of covariate coefficients and the long-term survivor proportion are obtained by the partial likelihood method, and their asymptotic properties are also established. Simulation studies demonstrate the performance of the proposed estimators, and an application to a real dataset is provided. 展开更多
关键词 semiparametric proportional hazards models left-truncated and right-censored data long-termsurvivors
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ASYMPTOTIC NORMALITY OF THE NONPARAMETRIC KERNEL ESTIMATION OF THE CONDITIONAL HAZARD FUNCTION FOR LEFT-TRUNCATED AND DEPENDENT DATA
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作者 Meijuan Ou Xianzhu Xiong Yi Wang 《Annals of Applied Mathematics》 2018年第4期395-406,共12页
Under some mild conditions, we derive the asymptotic normality of the Nadaraya-Watson and local linear estimators of the conditional hazard function for left-truncated and dependent data. The estimators were proposed ... Under some mild conditions, we derive the asymptotic normality of the Nadaraya-Watson and local linear estimators of the conditional hazard function for left-truncated and dependent data. The estimators were proposed by Liang and Ould-Sa?d [1]. The results confirm the guess in Liang and Ould-Sa?d [1]. 展开更多
关键词 asymptotic normality Nadaraya-Watson estimation local linear estimation conditional hazard function left-truncated data
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LOCAL POLYNOMIAL DOUBLE-SMOOTHING ESTIMATION OF A CONDITIONAL DISTRIBUTION FUNCTION WITH DEPENDENT
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作者 Mimi Hong Xianzhu Xiong 《Annals of Applied Mathematics》 2017年第4期364-378,共15页
Based on the idea of local polynomial double-smoother, we propose an estimator of a conditional cumulative distribution function with dependent and left-truncated data. It is assumed that the observations form a stati... Based on the idea of local polynomial double-smoother, we propose an estimator of a conditional cumulative distribution function with dependent and left-truncated data. It is assumed that the observations form a stationary a-mixing sequence. Asymptotic normality of the estimator is established. The finite sample behavior of the estimator is investigated via simulations. 展开更多
关键词 local polynomial double-smoother conditional cumulative distribution function left-truncated data a-mixing asymototic normality
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