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A Positive Stable Frailty Model for Clustered Failure Time Data with Covariate-Dependent Frailty

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  • Dandan Liu
  • John D. Kalbfleisch
  • Douglas E. Schaubel

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  • Dandan Liu & John D. Kalbfleisch & Douglas E. Schaubel, 2011. "A Positive Stable Frailty Model for Clustered Failure Time Data with Covariate-Dependent Frailty," Biometrics, The International Biometric Society, vol. 67(1), pages 8-17, March.
    • Handle: RePEc:bla:biomet:v:67:y:2011:i:1:p:8-17
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2010.01444.x
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    References listed on IDEAS

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    1. Zengri Wang & Thomas A. Louis, 2004. "Marginalized Binary Mixed-Effects Models with Covariate-Dependent Random Effects and Likelihood Inference," Biometrics, The International Biometric Society, vol. 60(4), pages 884-891, December.
    2. D. V. Glidden & S. G. Self, 1999. "Semiparametric Likelihood Estimation in the Clayton–Oakes Failure Time Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 26(3), pages 363-372, September.
    3. Christian Bressen Pipper & Torben Martinussen, 2003. "A Likelihood Based Estimating Equation for the Clayton–Oakes Model with Marginal Proportional Hazards," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(3), pages 509-521, September.
    4. Jason P. Fine & David V. Glidden & Kristine E. Lee, 2003. "A simple estimator for a shared frailty regression model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 317-329, February.
    5. Patrick J. Heagerty, 1999. "Marginally Specified Logistic-Normal Models for Longitudinal Binary Data," Biometrics, The International Biometric Society, vol. 55(3), pages 688-698, September.
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    Cited by:

    1. Giorgos Bakoyannis & Dipankar Bandyopadhyay, 2022. "Nonparametric tests for multistate processes with clustered data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(5), pages 837-867, October.

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