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Advances in Modeling Model Discrepancy: Comment on Wu and Browne (2015)

Published online by Cambridge University Press:  01 January 2025

Robert C. MacCallum  and
Anthony O’Hagan
Robert C. MacCallum*
Affiliation:
University of North Carolina at Chapel Hill
Anthony O’Hagan
Affiliation:
University of Sheffield
*
Correspondence should be made to Robert C. MacCallum, Department of Psychology, University of North Carolina at Chapel Hill, Davie Hall CB# 3270, Chapel Hill, NC 27599-3270 USA. Email: rcm@email.unc.edu
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Abstract

Wu and Browne (Psychometrika, 79, 2015) have proposed an innovative approach to modeling discrepancy between a covariance structure model and the population that the model is intended to represent. Their contribution is related to ongoing developments in the field of Uncertainty Quantification (UQ) on modeling and quantifying effects of model discrepancy. We provide an overview of basic principles of UQ and some relevant developments and we examine the Wu–Browne work in that context. We view the Wu–Browne contribution as a seminal development providing a foundation for further work on the critical problem of model discrepancy in statistical modeling in psychological research.

Keywords

model discrepancymodel errorUncertainty Quantificationcovariance structure modelingstructural equation modeling
Type
Original Paper
Information
Psychometrika , Volume 80 , Issue 3 , September 2015 , pp. 601 - 607
Copyright
Copyright © 2014 The Psychometric Society

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