A Comparison of Item Response Theory and Confirmatory Factor Analytic Methodologies for Establishing Measurement Equivalence/Invariance

By Adam W. Meade, G. Lautenschlager. 2004

306 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/51984dbad5c22aa89f05238835547ad48ce69f5b

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Citations in the corpus

Testing measurement invariance of composites using partial least squares (2016, background): “Over the last decades, research suggested a wide array of methods to assess various aspects of measurement invariance (e.g. Jong et al., 2007; Meade and Lautenschlager, 2004; Morris and Pavett, 1992; Raju et al., 2002; Raykov and Calantone, 2014; Salzberger and Sinkovics, 2006).”
Generational Differences in Work Ethic: An Examination of Measurement Equivalence Across Three Cohorts (2010, background): “While a full comparison of CFA and IRT approaches is beyond the scope of this study, IRT-based approaches offer advantages for itemlevel comparisons as well as allowing test or scale level comparisons (Meade and Lautenschlager 2004; Zickar and Broadfoot 2009).”
Measurement Invariance Conventions and Reporting: The State of the Art and Future Directions for Psychological Research (2016, methodology): “Readers interested in the IRT approach are referred to Tay, Meade, and Cao (2015) for an overview and tutorial, and Meade and Lautenschlager (2004) for a comparison of the SEM-CFA and IRT approaches.”
Assessing the Hypothesis of Measurement Invariance in the Context of Large-Scale International Surveys (2014, background): “…from previous simulation research that examined measurement invariance issues (Cheung & Rensvold, 2002; French & Finch, 2006; Lubke & Muthén, 2004; Meade & Lautenschlager, 2004); however, they better represented empirical data structures in the international studies of interest including TALIS,…”
Testing Factorial Invariance in Multilevel Data: A Monte Carlo Study (2012, unknown): “5 difference) was considered a large effect size in the factorial invariance literature (eg, French & Finch, 2008 ; Meade & Lautenschlager, 2004 ; Stark, Chernyshenko, & Drasgow, 2006 ).”
Testing Measurement Invariance Using MIMIC (2012, methodology): “A large volume of literature is devoted to the comparison of IRT and SEM with regard to measurement invariance testing (e.g., Meade & Lautenschlager, 2004; Raju, Laffitte, & Byrne, 2002; Stark, Chernyshenko, & Drasgow, 2006; Willse & Goodman, 2008).”
The Measurement Equivalence of Web-Based and Paper-and-Pencil Measures of Transformational Leadership (2006, methodology): “Finally, MGCFA equivalence analyses, compared to their IRT counterpart, test across groups simultaneously and therefore are preferred when multiple groups are being compared (as was the case in several of our analyses) and sample sizes are small ( Meade & Lautenschlager, 2004a ).”
Testing Measurement Invariance: A Comparison of Multiple-Group Categorical CFA and IRT (2011, methodology): “Thus, Meade and Lautenschlager (2004) stated that “in some cases, [IRT] can provide different and potentially more useful information for the establishment of measurement invariance” (p. 362; see also McDonald, 1999; Oishi, 2006; Raju et al., 2002; Reise et al., 1993).”
Development of the Competitive Work Environment Scale: A Multidimensional Climate Construct (2010, methodology): “Netemeyer et al. (2003) suggest initial exploratory factor analyses be conducted for the purposes of item trimming and initial psychometric analysis.”
Crowdsourcing and personality measurement equivalence: A warning about countries whose primary language is not English (2015, background): “…researchers have identified MACS as the most adequate way to assess measurement invariance across subgroups when the measure at hand is multidimensional (Meade & Lautenschlager, 2004) and when sample size varies between 500 and 1000 (Stark, Chernyshenko, & Drasgow, 2006), as in the current study.”
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).”
An Overview and Practical Guide to IRT Measurement Equivalence Analysis (2015, methodology): “However, the additional parameters per item afforded by IRT methods can result in more sensitivity to nuanced group differences such as differences in central tendency or the use of extreme scores (Meade & Lautenschlager, 2004).”
Researching Measurement Equivalence in Cross-Cultural Studies (2010, methodology): “The intercept parameters, on the other hand, have only a similar interpretation in the IRT and MLCA approach, but are not directly comparable with those in the MCFA approach (Meade & Lautenschlager, 2004).”