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Multiple Imputation and Posterior Simulation for Multivariate Missing Data in Longitudinal Studies

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  • Minzhi Liu
  • Jeremy M. G. Taylor
  • Thomas R. Belin

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  • Minzhi Liu & Jeremy M. G. Taylor & Thomas R. Belin, 2000. "Multiple Imputation and Posterior Simulation for Multivariate Missing Data in Longitudinal Studies," Biometrics, The International Biometric Society, vol. 56(4), pages 1157-1163, December.
    • Handle: RePEc:bla:biomet:v:56:y:2000:i:4:p:1157-1163
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2000.01157.x
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    References listed on IDEAS

    as
    1. Schenker, Nathaniel & Taylor, Jeremy M. G., 1996. "Partially parametric techniques for multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 22(4), pages 425-446, August.
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    Cited by:

    1. Shin Yongyun & Raudenbush Stephen W., 2013. "Efficient Analysis of Q-Level Nested Hierarchical General Linear Models Given Ignorable Missing Data," The International Journal of Biostatistics, De Gruyter, vol. 9(1), pages 109-133, September.
    2. Stuart R. Lipsitz & Garrett M. Fitzmaurice & Roger D. Weiss, 2020. "Using Multiple Imputation with GEE with Non-monotone Missing Longitudinal Binary Outcomes," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 890-904, December.
    3. Yongyun Shin & Stephen W. Raudenbush, 2011. "The Causal Effect of Class Size on Academic Achievement," Journal of Educational and Behavioral Statistics, , vol. 36(2), pages 154-185, April.
    4. Michael Kenward & James Carpenter, 2009. "Comments on: Missing data methods in longitudinal studies: a review," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(1), pages 65-67, May.
    5. Christopher H. Morrell & Larry J. Brant & Shan Sheng & E. Jeffrey Metter, 2012. "Screening for prostate cancer using multivariate mixed-effects models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(6), pages 1151-1175, November.
    6. Yongyun Shin & Stephen W. Raudenbush, 2007. "Just-Identified Versus Overidentified Two-Level Hierarchical Linear Models with Missing Data," Biometrics, The International Biometric Society, vol. 63(4), pages 1262-1268, December.

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