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Inference in Mixed Proportional Hazard Models with K Random Effects

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  • Guillaume Horny.

Abstract

A general formulation of Mixed Proportional Hazard models with K random effects is provided. It enables to account for a population stratified at K different levels. We then show how to approximate the partial maximum likelihood estimator using an EM algorithm. In a Monte Carlo study, the behavior of the estimator is assessed and I provide an application to the ratification of ILO conventions. Compared to other procedures, the results indicate an important decrease in computing time, as well as improved convergence and stability.

Suggested Citation

  • Guillaume Horny., 2009. "Inference in Mixed Proportional Hazard Models with K Random Effects," Working papers 248, Banque de France.
    • Handle: RePEc:bfr:banfra:248
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    References listed on IDEAS

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    1. Christian Gouriéroux & Irina Peaucelle, 1990. "Hétérogénéité - 1. Etude des biais d'estimation dans le cas linéaire," Annals of Economics and Statistics, GENES, issue 17, pages 163-183.
    2. repec:adr:anecst:y:1990:i:17:p:07 is not listed on IDEAS
    3. Guillaume Horny & Dragana Djurdjevic & Bernhard Boockmann & François Laisney, 2008. "Bayesian Estimation of Cox Models with Non-nested Random Effects: an Application to the Ratification Of ILO Conventions by Developing Countries," Annals of Economics and Statistics, GENES, issue 89, pages 193-214.
    4. Van den Berg, Gerard J., 2001. "Duration models: specification, identification and multiple durations," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 55, pages 3381-3460, Elsevier.
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    9. Vu, Hien T. V., 2004. "Estimation in semiparametric conditional shared frailty models with events before study entry," Computational Statistics & Data Analysis, Elsevier, vol. 45(3), pages 621-637, April.
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    13. Bernhard Boockmann, 2001. "The ratification of ILO conventions: A hazard rate analysis," Economics and Politics, Wiley Blackwell, vol. 13(3), pages 281-309, November.
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    Cited by:

    1. Guillaume Horny & Dragana Djurdjevic & Bernhard Boockmann & François Laisney, 2008. "Bayesian Estimation of Cox Models with Non-nested Random Effects: an Application to the Ratification Of ILO Conventions by Developing Countries," Annals of Economics and Statistics, GENES, issue 89, pages 193-214.
    2. J. Jarrahiferiz & M. Kayid & S. Izadkhah, 2019. "Stochastic properties of a weighted frailty model," Statistical Papers, Springer, vol. 60(1), pages 53-72, February.
    3. Yang Lu, 2020. "The distribution of unobserved heterogeneity in competing risks models," Statistical Papers, Springer, vol. 61(2), pages 681-696, April.

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    More about this item

    Keywords

    EM algorithm; penalized likelihood; partial likelihood; frailties.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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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