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Testing multivariate mean collinearity via latent variable modelling

Authors

  • Tenko Raykov,

    Corresponding author
    1. Michigan State University, East Lansing, USA
      Correspondence should be addressed to Dr Tenko Raykov, Measurement and Quantitative Methods, Michigan State University, East Lansing, MI 48824, USA (e-mail: raykov@msu.edu).
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  • Spiridon Penev

    1. University of New South Wales, Sydney, Australia
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Correspondence should be addressed to Dr Tenko Raykov, Measurement and Quantitative Methods, Michigan State University, East Lansing, MI 48824, USA (e-mail: raykov@msu.edu).

Abstract

A procedure for testing mean collinearity in multidimensional spaces is outlined, which is applicable in settings with missing data and can be used when examining group mean differences. The approach is based on non-linear parameter restrictions and is developed within the framework of latent variable modelling. The method provides useful information about the constellation of multiple response centroids in the populations studied, and is illustrated with an example.

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