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Latent Pattern Mixture Models for Informative Intermittent Missing Data in Longitudinal Studies

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  • Haiqun Lin
  • Charles E. McCulloch
  • Robert A. Rosenheck

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  • Haiqun Lin & Charles E. McCulloch & Robert A. Rosenheck, 2004. "Latent Pattern Mixture Models for Informative Intermittent Missing Data in Longitudinal Studies," Biometrics, The International Biometric Society, vol. 60(2), pages 295-305, June.
    • Handle: RePEc:bla:biomet:v:60:y:2004:i:2:p:295-305
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2004.00173.x
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    References listed on IDEAS

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    1. Paul S. Albert & Dean A. Follmann & Shaohua A. Wang & Edward B. Suh, 2002. "A Latent Autoregressive Model for Longitudinal Binary Data Subject to Informative Missingness," Biometrics, The International Biometric Society, vol. 58(3), pages 631-642, September.
    2. Jason Roy, 2003. "Modeling Longitudinal Data with Nonignorable Dropouts Using a Latent Dropout Class Model," Biometrics, The International Biometric Society, vol. 59(4), pages 829-836, December.
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    Cited by:

    1. Bartolucci, Francesco & Giorgio E., Montanari & Pandolfi, Silvia, 2012. "Item selection by an extended Latent Class model: An application to nursing homes evaluation," MPRA Paper 38757, University Library of Munich, Germany.
    2. Dantan Etienne & Proust-Lima Cécile & Letenneur Luc & Jacqmin-Gadda Helene, 2008. "Pattern Mixture Models and Latent Class Models for the Analysis of Multivariate Longitudinal Data with Informative Dropouts," The International Journal of Biostatistics, De Gruyter, vol. 4(1), pages 1-28, July.
    3. Jung, Hyekyung & Schafer, Joseph L. & Seo, Byungtae, 2011. "A latent class selection model for nonignorably missing data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 802-812, January.
    4. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
    5. Robert M. Elashoff & Gang Li & Ning Li, 2008. "A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types," Biometrics, The International Biometric Society, vol. 64(3), pages 762-771, September.
    6. Wei Zhao & Limin Peng & John Hanfelt, 2022. "Semiparametric latent class analysis of recurrent event data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1175-1197, September.
    7. Han, Jun, 2009. "Initial classification of joint data in EM estimation of latent class joint model," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2313-2323, November.
    8. Jouni Kuha & Myrsini Katsikatsou & Irini Moustaki, 2018. "Latent variable modelling with non‐ignorable item non‐response: multigroup response propensity models for cross‐national analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1169-1192, October.
    9. Proust-Lima, Cécile & Joly, Pierre & Dartigues, Jean-François & Jacqmin-Gadda, Hélène, 2009. "Joint modelling of multivariate longitudinal outcomes and a time-to-event: A nonlinear latent class approach," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1142-1154, February.
    10. Yu Liang & Wenbin Lu & Zhiliang Ying, 2009. "Joint Modeling and Analysis of Longitudinal Data with Informative Observation Times," Biometrics, The International Biometric Society, vol. 65(2), pages 377-384, June.
    11. Hélène Jacqmin-Gadda & Cécile Proust-Lima & Jeremy M.G. Taylor & Daniel Commenges, 2010. "Score Test for Conditional Independence Between Longitudinal Outcome and Time to Event Given the Classes in the Joint Latent Class Model," Biometrics, The International Biometric Society, vol. 66(1), pages 11-19, March.
    12. Charles E. McCulloch & John M. Neuhaus & Rebecca L. Olin, 2016. "Biased and unbiased estimation in longitudinal studies with informative visit processes," Biometrics, The International Biometric Society, vol. 72(4), pages 1315-1324, December.
    13. 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.
    14. Michael J. Daniels & Minji Lee & Wei Feng, 2023. "Dirichlet process mixture models for the analysis of repeated attempt designs," Biometrics, The International Biometric Society, vol. 79(4), pages 3907-3915, December.

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