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Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics

Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics Several issues relating to goodness of fit in structural equations are examined. The convergence and differentiation criteria, as applied by Bagozzi, are shown not to stand up under mathematical or statistical analysis. The authors argue that the choice of interpretative statistic must be based on the research objective. They demonstrate that when this is done the Fornell-Larcker testing system is internally consistent and that it conforms to the rules of correspondence for relating data to abstract variables. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Marketing Research SAGE

Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics

Journal of Marketing Research , Volume 18 (3): 7 – Aug 1, 1981

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References (21)

Publisher
SAGE
Copyright
© 1981 American Marketing Association
ISSN
0022-2437
eISSN
1547-7193
DOI
10.1177/002224378101800313
Publisher site
See Article on Publisher Site

Abstract

Several issues relating to goodness of fit in structural equations are examined. The convergence and differentiation criteria, as applied by Bagozzi, are shown not to stand up under mathematical or statistical analysis. The authors argue that the choice of interpretative statistic must be based on the research objective. They demonstrate that when this is done the Fornell-Larcker testing system is internally consistent and that it conforms to the rules of correspondence for relating data to abstract variables.

Journal

Journal of Marketing ResearchSAGE

Published: Aug 1, 1981

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