Statistical Inference of a Bivariate Proportional Hazard Model with Grouped Data
AbstractThis 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.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 9611005.
Length: 22 pages
Date of creation: 17 Nov 1996
Date of revision:
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Proportional Hazard; Bivariate Durations; Grouped Data;
Other versions of this item:
- An, Mark Yuying, 1996. "Statistical Inference of a Bivariate Proportional Hazard Model with Grouped Data," Working Papers 96-06, Duke University, Department of Economics.
- Yuying An, M., 1998. "Statistical Inference of a Bivariate Proportional Hazard Model with Grouped Data," Papers 98-12, Centre for Labour Market and Social Research, Danmark-.
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- An, Mark Yuying, 1996.
"Semiparametric Estimation of Willingness to Pay Distributions,"
96-20, Duke University, Department of Economics.
- Mark Yuying An, 1996. "Semiparametric Estimation of Willingness to Pay Distributions," Econometrics 9611001, EconWPA.
- An, Mark Yuying & Ayala, Roberto A., 1996.
"Nonparametric Estimation of a Survivor Function with Across-Interval-Censored Data,"
96-02, Duke University, Department of Economics.
- Mark Yuying An & Roberto Ayala, 1996. "Nonparametric Estimation of a Survivor Function with Across- Interval-Censored Data," Econometrics 9611003, EconWPA.
- Ortega, J., 2000.
"Job Rotation as a Mechanism for Learning,"
00-04, Centre for Labour Market and Social Research, Danmark-.
- Mark Yuying An, 2004. "Likelihood-Based Estimation of a Proportional-Hazard, Competing- Risk Model with Grouped Duration Data," Urban/Regional 0407013, EconWPA.
- 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.
- 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.
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