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Statistical Inference of a Bivariate Proportional Hazard Model with Grouped Data

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  • Mark Yuying An

    (Duke Uniersity)

Abstract

This paper studies the estimation of a semiparametric bivariate proportional hazard model from event time data under interval censoring. As a direct generalization of the bivariate exponential distribution of Marshall and Olkin, the model, on the one hand, controls for the effects of observed covariates, and on the other, achieves great flexibility through nonparametrically specified baseline hazards. The model is most relevant in analyzing the joint distribution of two event times arising from "systems of two components". Examples include the two infection times of the left and the right kidneys of patients and the two retirement times of married couples. To estimate this semiparametric model from grouped data, we propose a maximum likelihood estimator and a minimum chi-square estimator. Both estimation methods exploit the fact that the most flexible model structure that can be identified with grouped data is finite-dimensional. Compared with the maximum likelihood estimation, the minimum chi-square procedure is computationally more attractive but applies only to "many observations per cell" cases where the covariates are either categorical or amendable to sensible grouping. Specification tests for different model assumptions are also discussed.

(This abstract was borrowed from another version of this item.)

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Bibliographic Info

Paper provided by EconWPA in its series Econometrics with number 9611005.

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Length: 22 pages
Date of creation: 17 Nov 1996
Date of revision:
Handle: RePEc:wpa:wuwpem:9611005

Note: Type of Document - laTex; prepared on UNIX Sparc TeX; to print on PostScript; pages: 22 ; figures: request from author. We never published this piece and now we would like to reduce our mailing and xerox cost by posting it.
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Related research

Keywords: Proportional Hazard; Bivariate Durations; Grouped Data;

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References

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  1. An, Mark Yuying, 1996. "Semiparametric Estimation of Willingness to Pay Distributions," Working Papers 96-20, Duke University, Department of Economics.
  2. Mark Yuying An & Roberto Ayala, 1996. "Nonparametric Estimation of a Survivor Function with Across- Interval-Censored Data," Econometrics 9611003, EconWPA.
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Cited by:
  1. Mark Yuying An, 2004. "Likelihood-Based Estimation of a Proportional-Hazard, Competing- Risk Model with Grouped Duration Data," Urban/Regional 0407013, EconWPA.
  2. Pedersen, Peder J. & Smith, Nina, 2001. "International Migration and Migration policy in Denmark," CLS Working Papers 01-5, University of Aarhus, Aarhus School of Business, Centre for Labour Market and Social Research.
  3. Ortega, J., 2000. "Job Rotation as a Mechanism for Learning," Papers 00-04, Centre for Labour Market and Social Research, Danmark-.
  4. Westergaard-Nielsen, Niels, 2001. "Danish Labour Market Policy: Is it worth it?," CLS Working Papers 01-10, University of Aarhus, Aarhus School of Business, Centre for Labour Market and Social Research.
  5. Ramkishen S. Rejan, 1998. "The Currency And Financial Crisis In Southeast Asia - A Case Of `Sudden Deathã¢Â‚¬Â„¢ Or `Death Foretoldã¢Â‚¬Â„¢," Macroeconomics Working Papers 22381, East Asian Bureau of Economic Research.

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