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Maximum likelihood and generalized least squares analyses of two-level structural equation models

Author

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  • Poon, Wai-Yin
  • Lee, Sik-Yum

Abstract

A two-level structural equation model with small level-one samples and unbalanced designs is treated. Under the assumption of normality, the maximum likelihood and generalized least squares methods are employed to analyze the model. Asymptotic properties of the estimators are discussed. Results of a Monte Carlo study investigating the performance of the estimators are reported.

Suggested Citation

  • Poon, Wai-Yin & Lee, Sik-Yum, 1992. "Maximum likelihood and generalized least squares analyses of two-level structural equation models," Statistics & Probability Letters, Elsevier, vol. 14(1), pages 25-30, May.
    • Handle: RePEc:eee:stapro:v:14:y:1992:i:1:p:25-30
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    Cited by:

    1. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "Generalized multilevel structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 167-190, June.
    2. Anders Skrondal & Sophia Rabe‐Hesketh, 2007. "Latent Variable Modelling: A Survey," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 712-745, December.

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