Error in Variables – Analysis of Covariance Structure

  • Hubert Gatignon


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


Confirmatory Factor Analysis Measurement Model Covariance Structure Canonical Correlation Canonical Correlation Analysis 
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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.INSEAD, The Business School for the WorldFontainebleau CedexFrance

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