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Joint modeling of cross-sectional health outcomes and longitudinal predictors via mixtures of means and variances

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  • Bei Jiang
  • Michael R. Elliott
  • Mary D. Sammel
  • Naisyin Wang

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  • Bei Jiang & Michael R. Elliott & Mary D. Sammel & Naisyin Wang, 2015. "Joint modeling of cross-sectional health outcomes and longitudinal predictors via mixtures of means and variances," Biometrics, The International Biometric Society, vol. 71(2), pages 487-497, June.
    • Handle: RePEc:bla:biomet:v:71:y:2015:i:2:p:487-497
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    File URL: http://hdl.handle.net/10.1111/biom.12284
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    References listed on IDEAS

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    1. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    2. Matthew Stephens, 2000. "Dealing with label switching in mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 795-809.
    3. Elizabeth S. Garrett & Scott L. Zeger, 2000. "Latent Class Model Diagnosis," Biometrics, The International Biometric Society, vol. 56(4), pages 1055-1067, December.
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    Cited by:

    1. Rui Martins, 2022. "A flexible link for joint modelling longitudinal and survival data accounting for individual longitudinal heterogeneity," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 41-61, March.

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