Power and Precision in Confirmatory Factor Analytic Tests of Measurement Invariance

By Adam W. Meade, Daniel J. Bauer. 2007

224 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Food Science, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/0e2a374219e6751cc0e535f093564fa04dff0d71

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Citations in the corpus

Measurement Equivalence of Ordinal Items: A Comparison of Factor Analytic, Item Response Theory, and Latent Class Approaches (2011, methodology): “…of the CFA and IRT methods is the sample size, i.e., because of lack of power a smaller sample size reduces the ability of the two approaches to detect inequivalence in data (Meade and Lautenschlager, 2004a; Meade and Bauer, 2007; French and Finch, 2006; Meade and Lautenschlager, 2004b).”
A Direct Comparison Approach for Testing Measurement Invariance (2012, methodology): “…sample size, the number of items per factor, item communality (the proportion of variance in an item explained by the latent factor), and the size of the factor loading (a ratio to the factor loading of the referent) may play a critical role (Meade & Bauer, 2007; Meade & Lautenschlager, 2004b).”
The structure of executive function in 3-year-old children (2010, unknown): “To explore the sources of variance in measurement, a partial invariance model was tested by constraining each indicator error variance to equality individually for each EF task indicator in turn (Byrne, Shavelson, & Muthen, 1989; Meade & Bauer, 2007).”
An Investigation of the Alignment Method With Polytomous Indicators Under Conditions of Partial Measurement Invariance (2018, methodology): “…of choosing an anchor item for model identification (Johnson, Meade, & DuVernet, 2009; Wang & Yeh, 2003), selecting the best way to compare model fit (Cheung & Rensvold, 2002; French & Finch, 2006), and ensuring adequate power (Cohen, Kim, & Wollack, 1996; Kaplan, 1989; Meade & Bauer, 2007).”
Comparisons of Three Empirical Methods for Partial Factorial Invariance: Forward, Backward, and Factor-Ratio Tests (2016, background): “However, the majority of the measurement invariance studies have considered only metric invariance (i.e., factor loading invariance) as one of the simulation conditions (French & Finch, 2008; Meade & Bauer, 2007; Meade & Lautenschlager, 2004).”
Evaluating Model Fit With Ordered Categorical Data Within a Measurement Invariance Framework: A Comparison of Estimators (2014, methodology): “Similar to the χ2, the χ2 might be limited due to sensitivity to large sample sizes, model complexity, nonnormal data, and model misspecification (Asparouhov & Muthén, 2006; French & Finch, 2008; Meade & Bauer, 2007; Yuan & Bentler, 2004).”
Testing Factorial Invariance in Multilevel Data: A Monte Carlo Study (2012, background): “Measurement invariance has gained attention in different social science disciplines since the breakthrough of Mellenbergh (1989) and Meredith (1993) and the systematic review on this topic by Vandenberg and Lance (2000).”