articleTop 10% cited
Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics
Journal of Marketing Research · 1981 · Vol. 18(3) · pp. 382–388
Claes Fornell✉(University of Michigan–Ann Arbor)David F. Larcker(Kellogg's (Canada))
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.
Advanced Statistical Methods and ModelsMulti-Criteria Decision MakingStatistical Methods and ApplicationsUnobservableStatisticStructural equation modelingGoodness of fitStatisticsMathematicsEconometricsMathematical statisticsConvergence (economics)Applied mathematics
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References
Evaluating Structural Equation Models with Unobservable Variables and Measurement Error
Journal of Marketing Research · 1981 · 64,985 citations
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