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Statistical Analysis of Management Data pp 297–348Cite as

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

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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.

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Authors and Affiliations

  1. INSEAD, Fontainebleau Cedex, France

    Hubert Gatignon

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  1. Hubert Gatignon
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Gatignon, H. (2014). Error in Variables: Analysis of Covariance Structure – Structural Equation Models. In: Statistical Analysis of Management Data. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-8594-0_10

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