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Marginally Specified Generalized Linear Mixed Models: A Robust Approach

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  • J. E. Mills
  • C. A. Field
  • D. J. Dupuis

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  • J. E. Mills & C. A. Field & D. J. Dupuis, 2002. "Marginally Specified Generalized Linear Mixed Models: A Robust Approach," Biometrics, The International Biometric Society, vol. 58(4), pages 727-734, December.
    • Handle: RePEc:bla:biomet:v:58:y:2002:i:4:p:727-734
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2002.00727.x
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    References listed on IDEAS

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    1. 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.
    2. J. G. Booth & J. P. Hobert, 1999. "Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 265-285.
    3. John S. Preisser & Bahjat F. Qaqish, 1999. "Robust Regression for Clustered Data with Application to Binary Responses," Biometrics, The International Biometric Society, vol. 55(2), pages 574-579, June.
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    Cited by:

    1. Eva Cantoni & Joanna Mills Flemming & Elvezio Ronchetti, 2005. "Variable Selection for Marginal Longitudinal Generalized Linear Models," Biometrics, The International Biometric Society, vol. 61(2), pages 507-514, June.
    2. Guo You Qin & Zhong Yi Zhu, 2009. "Robustified Maximum Likelihood Estimation in Generalized Partial Linear Mixed Model for Longitudinal Data," Biometrics, The International Biometric Society, vol. 65(1), pages 52-59, March.
    3. Bellio, Ruggero, 2007. "Algorithms for bounded-influence estimation," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2531-2541, February.
    4. Liu, Anna & Qin, Li & Staudenmayer, John, 2010. "M-type smoothing spline ANOVA for correlated data," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2282-2296, November.

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