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Multivariate Effect Size Estimation: Confidence Interval Construction via Latent Variable Modeling

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  • Tenko Raykov
  • George A. Marcoulides

Abstract

A latent variable modeling method is outlined for constructing a confidence interval (CI) of a popular multivariate effect size measure. The procedure uses the conventional multivariate analysis of variance (MANOVA) setup and is applicable with large samples. The approach provides a population range of plausible values for the proportion of generalized variance associated with group membership and permits at the same time testing of the underlying assumption of covariance matrix homogeneity. The method is generally applicable, is most readily used in empirical research with up to three simultaneously analyzed response variables, and is illustrated with an empirical example.

Suggested Citation

  • Tenko Raykov & George A. Marcoulides, 2010. "Multivariate Effect Size Estimation: Confidence Interval Construction via Latent Variable Modeling," Journal of Educational and Behavioral Statistics, , vol. 35(4), pages 407-421, August.
    • Handle: RePEc:sae:jedbes:v:35:y:2010:i:4:p:407-421
    DOI: 10.3102/1076998609359792
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    References listed on IDEAS

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    1. Timm, Neil H., 2004. "Estimating Effect Sizes in Exploratory Experimental Studies When Using a Linear Model," The American Statistician, American Statistical Association, vol. 58, pages 213-217, August.
    2. David Rindskopf, 1984. "Using phantom and imaginary latent variables to parameterize constraints in linear structural models," Psychometrika, Springer;The Psychometric Society, vol. 49(1), pages 37-47, March.
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