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Error in Variables: Analysis of Covariance Structure – Structural Equation Models

  • Hubert Gatignon
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Abstract

In this chapter, we bring together the notions of measurement error discussed in Chaps. 3 and 4 with the structural modeling of simultaneous relationships presented in Chap. 6. We demonstrate that a bias is introduced when estimating the relationship between two variables measured with error if that measurement error is ignored. We then present a methodology for estimating the parameters of structural relationships between variables that are not observed directly: analysis of covariance structures. We focus on the role of the measurement model as discussed in Chap. 4 with the confirmatory factor analytic model.

Keywords

Confirmatory Factor Analysis Measurement Model Covariance Structure Canonical Correlation Analysis Canonical Variate 
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© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Hubert Gatignon
    • 1
  1. 1.INSEADFontainebleau CedexFrance

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