Partially linear hazard regression for multivariate survival data

Jianwen Cai Jianqing Fan Jiancheng Jiang Haibo Zhou

Statistics Theory and Methods mathscidoc:1912.43332

Journal of the American Statistical Association, 102, (478), 538-551, 2007.6
This article studies estimation of partially linear hazard regression models for multivariate survival data. A profile pseudopartial likelihood estimation method is proposed under the marginal hazard model framework. The estimation on the parameters for the linear part is accomplished by maximization of a pseudopartial likelihood profiled over the nonparametric part. This enables us to obtain-consistent estimators of the parametric component. Asymptotic normality is obtained for the estimates of both the linear and nonlinear parts. The new technical challenge is that the nonparametric component is indirectly estimated through its integrated derivative function from a local polynomial fit. An algorithm of fast implementation of our proposed method is presented. Consistent standard error estimates using sandwich-type ideas are also developed, which facilitates inferences for the model. It is shown that the
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@inproceedings{jianwen2007partially,
  title={Partially linear hazard regression for multivariate survival data},
  author={Jianwen Cai, Jianqing Fan, Jiancheng Jiang, and Haibo Zhou},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113748115276892},
  booktitle={Journal of the American Statistical Association},
  volume={102},
  number={478},
  pages={538-551},
  year={2007},
}
Jianwen Cai, Jianqing Fan, Jiancheng Jiang, and Haibo Zhou. Partially linear hazard regression for multivariate survival data. 2007. Vol. 102. In Journal of the American Statistical Association. pp.538-551. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113748115276892.
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