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Estimation in Varying-coefficient Proportional Hazard Regression Model

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Abstract

In this paper, varying coefficient proportional hazard regression models are considered. The model is an important extension of the Cox model, and arises naturally if the coefficients change over different groups characterized by certain covariates in practice. Under random censorship, weighted partial likelihood estimators are defined for the varying coefficients by maximizing weighted partial likelihoods. It is shown that the proposed estimators are consistent and asymptotically normal.

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Authors and Affiliations

  1. Academy of Mathematics and Systems Science, Chinese Academy of Science, Beijing, 100080, People’s Republic of China

    Qihua Wang & Lili Yao

  2. Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam, Hong Kong, People’s Republic of China

    Qihua Wang

Authors
  1. Qihua Wang
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  2. Lili Yao
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Correspondence to Qihua Wang.

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Wang, Q., Yao, L. Estimation in Varying-coefficient Proportional Hazard Regression Model. Metrika 64, 271–288 (2006). https://doi.org/10.1007/s00184-006-0048-9

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  • DOI: https://doi.org/10.1007/s00184-006-0048-9

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