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Joint Regression and Association Modeling of Longitudinal Ordinal Data

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  • Anders Ekholm
  • Jukka Jokinen
  • John W. McDonald
  • Peter W. F. Smith

Abstract

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Suggested Citation

  • Anders Ekholm & Jukka Jokinen & John W. McDonald & Peter W. F. Smith, 2003. "Joint Regression and Association Modeling of Longitudinal Ordinal Data," Biometrics, The International Biometric Society, vol. 59(4), pages 795-803, December.
  • Handle: RePEc:bla:biomet:v:59:y:2003:i:4:p:795-803
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2003.00093.x
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    References listed on IDEAS

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    1. Teugels, J. L. & Van Horebeek, J., 1998. "Algebraic Descriptions of Nominal Multivariate Discrete Data," Journal of Multivariate Analysis, Elsevier, vol. 67(2), pages 203-226, November.
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    Cited by:

    1. J. Perin & J. S. Preisser & C. Phillips & B. Qaqish, 2014. "Regression analysis of correlated ordinal data using orthogonalized residuals," Biometrics, The International Biometric Society, vol. 70(4), pages 902-909, December.
    2. Parsons, Nick R. & Costa, Matthew L. & Achten, Juul & Stallard, Nigel, 2009. "Repeated measures proportional odds logistic regression analysis of ordinal score data in the statistical software package R," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 632-641, January.
    3. Eiji Nakashima & Kazuo Neriishi & Atsushi Minamoto, 2008. "Comparison of methods for ordinal lens opacity data from atomic-bomb survivors: univariate worse-eye method and bivariate GEE method using global odds ratio," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(3), pages 465-482, September.
    4. Thomas Suesse & Ivy Liu, 2013. "Modelling Strategies for Repeated Multiple Response Data," International Statistical Review, International Statistical Institute, vol. 81(2), pages 230-248, August.

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