A Monte-Carlo Study of Confirmatory Factor Analytic Tests of Measurement Equivalence/Invariance

By Adam W. Meade, G. Lautenschlager. 2004

186 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/6158c9971a6cb6196f595826fdf5c17cb491165c

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In Computer Networks and Communications

In Management Science and Operations Research

Citations in the corpus

A Comparison of Item Response Theory and Confirmatory Factor Analytic Methodologies for Establishing Measurement Equivalence/Invariance (2004, background): “Moreover, in some situations, it is possible that ME/I tests could be misleading such as with CFA tests in which sample sizes are small, factor communalities are low (Meade & Lautenschlager, 2004), or differences that parallel those of b parameters are present.”
Measurement Equivalence of Ordinal Items: A Comparison of Factor Analytic, Item Response Theory, and Latent Class Approaches (2011, methodology): “As model selection measures we used the chi-square difference (or LR) test, which is common in CFA- and IRT-based procedures (Vandenberg and Lance, 2000; Meade & Lautenschlager, 2004a), and the AIC that is typically used in LCFA as well as in CFA (Kankaraš and Moors, forthcoming).”
Detecting Violations of Factorial Invariance Using Data-Based Specification Searches: A Monte Carlo Study (2007, methodology): “Meade and Lautenschlager (2004) conducted a Monte Carlo study to evaluate CFA tests for testing measurement invariance.”
Problems With Item Parceling for Confirmatory Factor Analytic Tests of Measurement Invariance (2006, methodology): “However, different types of parceling strategies will affect important properties such as communality, and these data properties will affect the power of MI tests (Meade & Lautenschlager, 2004a).”
Confirmatory Factor Analytic Procedures for the Determination of Measurement Invariance (2006, methodology): “The latter recommendation is beginning to be followed with the implementation of simulation studies (e.g., Meade & Lautenschlager, 2004).”
Measurement Invariance for Latent Constructs in Multiple Populations (2012, background): “Various aspects of this important limitation have received considerable attention in the recent literature on MI (e.g., Cheung & Rensvold, 1999; Little, 2000; Meade & Lautenschlager, 2004; Millsap, 2011; Rensvold & Cheung, 2001; Vandenberg & Lance, 2000; Woods, 2009; Yoon & Millsap, 2007).”
The Responses to Script-Driven Imagery Scale (RSDI): Assessment of State Posttraumatic Symptoms for Psychobiological and Treatment Research (2007, background): “cy (Meade and Lautenschlager 2004), communalities were generally high: Reexperiencing items, 0.”
Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance (2007, unknown): “(Meade & Lautenschlager, 2004).”
Evaluating Model Fit With Ordered Categorical Data Within a Measurement Invariance Framework: A Comparison of Estimators (2014, methodology): “However, this study elected to implement a 1 to 1 ratio using sample sizes of 150, 300, and 500 per group to complement the work of Cheung and Rensvold (2002), French and Finch (2008), Lubke and Muthén (2004), and Meade and Lautenschlager (2004).”
Multigroup Confirmatory Factor Analysis: Locating the Invariant Referent Sets (2008, background): “Researchers have addressed this issue to some degree (eg, French & Finch, 2006 ; Meade & Lautenschlager, 2004 ) and identified conditions in which these methods appear most effective.”
Power and Precision in Confirmatory Factor Analytic Tests of Measurement Invariance (2007, methodology): “In one published study, Meade and Lautenschlager (2004) simulated data for both a 6- and 12-item scale, then manipulated the number of items showing loading differences between simulated samples (sometimes called differential functioning [DF] items), and the directionality of the simulated…”
The Measurement Equivalence of Web-Based and Paper-and-Pencil Measures of Transformational Leadership (2006, methodology): “MGCFA is a powerful and versatile approach for testing measurement equivalence across applications (Cheung & Rensvold, 2002; Meade & Lautenschlager, 2004b; Steenkamp & Baumgartner, 1998; Vandenberg & Lance, 2000).”
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).”