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Inference in Mixed Proportional Hazard Models with K Random Effects

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Author Info
Guillaume Horny.

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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.

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Publisher Info
Paper provided by Banque de France in its series Documents de Travail with number 248.

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Length: 29 pages
Date of creation: 2009
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Handle: RePEc:bfr:banfra:248

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Related research
Keywords: EM algorithm; penalized likelihood; partial likelihood; frailties.;

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis

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References listed on IDEAS
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.:
  1. Bolstad W. M & Manda S. O, 2001. "Investigating Child Mortality in Malawi Using Family and Community Random Effects: A Bayesian Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 12-19, March. [Downloadable!] (restricted)
  2. Hien T.V. Vu & Matthew W. Knuiman, 2002. "Estimation in Semiparametric Marginal Shared Gamma Frailty Models," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 44(4), pages 489-501, December. [Downloadable!] (restricted)
  3. Pakes, Ariel, 1983. "On Group Effects and Errors in Variables in Aggregation," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 168-73, February. [Downloadable!] (restricted)
  4. Moulton, Brent R., 1986. "Random group effects and the precision of regression estimates," Journal of Econometrics, Elsevier, vol. 32(3), pages 385-397, August. [Downloadable!] (restricted)
  5. מחקר - ביטוח לאומי, 1990. "Volume 2," Working Papers 61, National Insurance Institute of Israel. [Downloadable!]
  6. Bernhard Boockmann, 2001. "The ratification of ILO conventions: A hazard rate analysis," Economics and Politics, Blackwell Publishing, vol. 13(3), pages 281-309, November. [Downloadable!] (restricted)
  7. 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. [Downloadable!] (restricted)
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  8. 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. [Downloadable!] (restricted)
  9. Vu, Hien T. V. & Knuiman, Matthew W., 2002. "A hybrid ML-EM algorithm for calculation of maximum likelihood estimates in semiparametric shared frailty models," Computational Statistics & Data Analysis, Elsevier, vol. 40(1), pages 173-187, July. [Downloadable!] (restricted)
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  1. Bernhard Boockmann. & Dragana Djurdjevic. & Guillaume Horny. & François Laisney., 2009. "Bayesian estimation of Cox models with non-nested random effects: an application to the ratification of ILO conventions by developing countries," Documents de Travail 249, Banque de France. [Downloadable!]
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This page was last updated on 2009-11-24.

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