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Just-Identified Versus Overidentified Two-Level Hierarchical Linear Models with Missing Data

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  • Yongyun Shin
  • Stephen W. Raudenbush

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  • 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.
    • Handle: RePEc:bla:biomet:v:63:y:2007:i:4:p:1262-1268
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    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2007.00818.x
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    References listed on IDEAS

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    1. 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.
    2. Joseph L. Schafer, 2003. "Multiple Imputation in Multivariate Problems When the Imputation and Analysis Models Differ," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 57(1), pages 19-35, February.
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    Cited by:

    1. Yongyun Shin & Stephen W. Raudenbush, 2010. "A Latent Cluster-Mean Approach to the Contextual Effects Model With Missing Data," Journal of Educational and Behavioral Statistics, , vol. 35(1), pages 26-53, February.
    2. 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.
    3. Yongyun Shin, 2012. "Do Black Children Benefit More From Small Classes? Multivariate Instrumental Variable Estimators With Ignorable Missing Data," Journal of Educational and Behavioral Statistics, , vol. 37(4), pages 543-574, August.
    4. Stephen A. Mistler & Craig K. Enders, 2017. "A Comparison of Joint Model and Fully Conditional Specification Imputation for Multilevel Missing Data," Journal of Educational and Behavioral Statistics, , vol. 42(4), pages 432-466, August.

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