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Average Derivatives For Hazard Functions

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  • G rgens, Tue

Abstract

This paper develops semiparametric kernel-based estimators of risk-specific hazard functions for competing risks data. Both discrete and continuous failure times are considered. The maintained assumption is that the hazard function depends on explanatory variables only through an index. In contrast to existing semiparametric estimators, proportional hazards is not assumed. The new estimators are asymptotically normally distributed. The estimator of index coefficients is root-n consistent. The estimator of hazard functions achieves the one-dimensional rate of convergence. Thus the index assumption eliminates the curse of dimensionality. The estimators perform well in Monte Carlo experiments.I thank Denise Doiron for stimulating my interest in this research project and Catherine de Fontenay, Hans Christian Kongsted, Lars Muus, seminar participants, and two anonymous referees for comments on an earlier version of the paper. I gratefully acknowledge the hospitality of the University of Aarhus and the University of Copenhagen, where part of this research was undertaken.

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Bibliographic Info

Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 20 (2004)
Issue (Month): 03 (June)
Pages: 437-463

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Handle: RePEc:cup:etheor:v:20:y:2004:i:03:p:437-463_20

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Cited by:
  1. Li, Jianbo & Zhang, Riquan, 2011. "Partially varying coefficient single index proportional hazards regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 389-400, January.
  2. Lu, Xuewen & Cheng, Tsung-Lin, 2007. "Randomly censored partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 98(10), pages 1895-1922, November.
  3. Lu, Xuewen, 2010. "Asymptotic distributions of two "synthetic data" estimators for censored single-index models," Journal of Multivariate Analysis, Elsevier, vol. 101(4), pages 999-1015, April.
  4. Sun, Jie & Kopciuk, Karen A. & Lu, Xuewen, 2008. "Polynomial spline estimation of partially linear single-index proportional hazards regression models," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 176-188, September.

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