In this paper we consider a class of semi-parametric transformation models, under which an unknown transformation of the survival time is linearly related to the covariates with various completely specified error distributions. This class of regression models includes the proportional hazards and proportional odds models. Inference procedures derived from a class of generalised estimating equations are proposed to examine the covariate effects with censored observations. Numerical studies are conducted to investigate the properties of our proposals for practical sample sizes. These transformation models, coupled with the new simple inference procedures, provide many useful alternatives to the Cox regression model in survival analysis.
机构:
Guangzhou Univ, Sch Econ & Stat, Guangzhou, Guangdong, Peoples R ChinaGuangzhou Univ, Sch Econ & Stat, Guangzhou, Guangdong, Peoples R China
Li, Shuwei
Hu, Tao
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Capital Normal Univ, Sch Math Sci, Beijing, Peoples R ChinaGuangzhou Univ, Sch Econ & Stat, Guangzhou, Guangdong, Peoples R China
Hu, Tao
Wang, Peijie
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Jilin Univ, Ctr Appl Stat Res, Changchun, Jilin, Peoples R China
Jilin Univ, Sch Math, Changchun, Jilin, Peoples R ChinaGuangzhou Univ, Sch Econ & Stat, Guangzhou, Guangdong, Peoples R China
Wang, Peijie
Sun, Jianguo
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Jilin Univ, Ctr Appl Stat Res, Changchun, Jilin, Peoples R China
Jilin Univ, Sch Math, Changchun, Jilin, Peoples R China
Univ Missouri, Dept Stat, Columbia, MO 65211 USAGuangzhou Univ, Sch Econ & Stat, Guangzhou, Guangdong, Peoples R China
机构:
Capital Normal Univ, Sch Math Sci, Beijing 100048, Peoples R China
Capital Normal Univ, BCMIIS, Beijing 100048, Peoples R ChinaCapital Normal Univ, Sch Math Sci, Beijing 100048, Peoples R China
Hu, Tao
Xiang, Liming
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Nanyang Technol Univ, Sch Phys & Math Sci, Singapore 637371, SingaporeCapital Normal Univ, Sch Math Sci, Beijing 100048, Peoples R China