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 Duke University, Department of Economics in its series Working Papers with number 96-06.
Date of creation: 1996
Date of revision:
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Other versions of this item:
- Mark Yuying An, 1996. "Statistical Inference of a Bivariate Proportional Hazard Model with Grouped Data," Econometrics 9611005, EconWPA.
- 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-.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
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