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Bayesian Latent-Class Mixed-Effect Hybrid Models for Dyadic Longitudinal Data with Non-Ignorable Dropouts

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  • Jaeil Ahn
  • Suyu Liu
  • Wenyi Wang
  • Ying Yuan

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  • Jaeil Ahn & Suyu Liu & Wenyi Wang & Ying Yuan, 2013. "Bayesian Latent-Class Mixed-Effect Hybrid Models for Dyadic Longitudinal Data with Non-Ignorable Dropouts," Biometrics, The International Biometric Society, vol. 69(4), pages 914-924, December.
    • Handle: RePEc:bla:biomet:v:69:y:2013:i:4:p:914-924
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    File URL: http://hdl.handle.net/10.1111/biom.12100
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    References listed on IDEAS

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    1. Jason Roy & Michael J. Daniels, 2008. "A General Class of Pattern Mixture Models for Nonignorable Dropout with Many Possible Dropout Times," Biometrics, The International Biometric Society, vol. 64(2), pages 538-545, June.
    2. Michael J. Daniels & Joseph W. Hogan, 2000. "Reparameterizing the Pattern Mixture Model for Sensitivity Analyses Under Informative Dropout," Biometrics, The International Biometric Society, vol. 56(4), pages 1241-1248, December.
    3. 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.
    4. Jason Roy & Xihong Lin, 2000. "Latent Variable Models for Longitudinal Data with Multiple Continuous Outcomes," Biometrics, The International Biometric Society, vol. 56(4), pages 1047-1054, December.
    5. Ying Yuan & Roderick J. A. Little, 2009. "Mixed-Effect Hybrid Models for Longitudinal Data with Nonignorable Dropout," Biometrics, The International Biometric Society, vol. 65(2), pages 478-486, June.
    6. D. M. Farewell, 2010. "Marginal analyses of longitudinal data with an informative pattern of observations," Biometrika, Biometrika Trust, vol. 97(1), pages 65-78.
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