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Empirical Bayes Estimation of Random Effects Parameters in Mixed Effects Logistic Regression Models

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  • Thomas R. Ten Have
  • A. Russell Localio

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  • Thomas R. Ten Have & A. Russell Localio, 1999. "Empirical Bayes Estimation of Random Effects Parameters in Mixed Effects Logistic Regression Models," Biometrics, The International Biometric Society, vol. 55(4), pages 1022-1029, December.
    • Handle: RePEc:bla:biomet:v:55:y:1999:i:4:p:1022-1029
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.1999.01022.x
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    Cited by:

    1. Anders Skrondal & Sophia Rabe‐Hesketh, 2009. "Prediction in multilevel generalized linear models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 659-687, June.
    2. Noh, Maengseok & Lee, Youngjo, 2007. "REML estimation for binary data in GLMMs," Journal of Multivariate Analysis, Elsevier, vol. 98(5), pages 896-915, May.
    3. R. H. Rieger & C. R. Weinberg, 2009. "Testing for violations of the homogeneity needed for conditional logistic regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(10), pages 1147-1157.
    4. Cristiano C. Santos & Rosangela H. Loschi, 2017. "Maximum likelihood estimation and parameter interpretation in elliptical mixed logistic regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 209-230, March.
    5. McMahon, James M. & Pouget, Enrique R. & Tortu, Stephanie, 2006. "A guide for multilevel modeling of dyadic data with binary outcomes using SAS PROC NLMIXED," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3663-3680, August.
    6. Randall H. Rieger & Clarice R. Weinberg, 2002. "Analysis of Clustered Binary Outcomes Using Within-Cluster Paired Resampling," Biometrics, The International Biometric Society, vol. 58(2), pages 332-341, June.
    7. Högberg, Hans & Svensson, Elisabeth, 2008. "An Overview of Methods in the Analysis of Dependent ordered catagorical Data: Assumptions and Implications," Working Papers 2008:7, Örebro University, School of Business.

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