The problem of allowing correlated errors in structural equation modeling: concerns and considerations
Results of structural equation models may be negated by inappropriate methodological procedures. Model fit is known to be improved by the addition of pathways. Some pathways are added due to modification indices. These a - theoretical pathways will improve model fit at the expense of theory and reduction in parameter value replication. Furthermore, some additions to the model like correlating measurement errors are usually theoretically unjustifiable. This quantitative review examines the frequency of correlating measurement errors and examines the reasons, if any, for having these pathways in the model. Additionally, this quantitative review examines the consequences of correlating measurement errors in structural equation modeling
Volume (Year): 3 (2015)
Issue (Month): 1 (June)
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- Gerbing, David W & Anderson, James C, 1984. " On the Meaning of Within-Factor Correlated Measurement Errors," Journal of Consumer Research, Oxford University Press, vol. 11(1), pages 572-580, June.
- James Anderson & David Gerbing, 1984. "The effect of sampling error on convergence, improper solutions, and goodness-of-fit indices for maximum likelihood confirmatory factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 49(2), pages 155-173, June.
- Fornell, Claes, 1983. " Issues in the Application of Covariance Structure Analysis: A Comment," Journal of Consumer Research, Oxford University Press, vol. 9(4), pages 443-448, March.
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