Do Self-Report Instruments Allow Meaningful Comparisons Across Diverse Population Groups?: Testing Measurement Invariance Using the Confirmatory Factor Analysis Framework

By S. Gregorich. Medical Care, 2006

860 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Social Psychology, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/ab5c2bdcfca131f9d6b40eb61a83d51676d911eb

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Citations in the corpus

Measuring Loneliness Among Middle-Aged and Older Adults: The UCLA and de Jong Gierveld Loneliness Scales (2014, background): “‘Strong’ invariance is present when both item factor loadings and intercepts are equivalent across groups, indicating that observed mean group differences reflect latent mean group differences (Gregorich 2006).”
Assessing students’ experiences of teaching–learning environments and approaches to learning: Validation of a questionnaire in different countries and varying contexts (2013, result): “The results indicate fair dimensional and configural invariance of the two data sets or, in other words, the same number of factors emerge and the same items are associated with the same underlying factors in both the Finnish and British data sets (Gregorich 2006).”
The basic psychological needs in exercise scale: Translation and evidence for cross‐cultural validity (2010, methodology): “Given strong factorial invariance, cross-group differences in observed means are assumed to be unbiased estimates of group differences in the corresponding latent factor means (Gregorich, 2006).”
University Instructors’ Achievement Goals for Teaching (2019, methodology): “The following models were compared (cf. Gregorich, 2006): (a) a model in which the item-factor clusters were restricted to be equivalent for all three groups (configural invariance), (b) a model in which the factor loadings were additionally restricted between the three groups (metric invariance),…”
lordif: An R Package for Detecting Differential Item Functioning Using Iterative Hybrid Ordinal Logistic Regression/Item Response Theory and Monte Carlo Simulations (2011, background): “2 lordif: IRT Hybrid Logistic Regression DIF in R is important prior to making comparisons among individuals or groups (Gregorich 2006).”
An Essay on Measurement and Factorial Invariance (2006, methodology): “For example, it is easy to see how 2 groups could exhibit no manifest mean differences on an item, i(1) i(2) 0 yet have differences in common and specific factor means such that ik k(1) ik k(2) ( i(1) i(2)).”
Are cognitive g and academic achievement g one and the same g? An exploration on the Woodcock–Johnson and Kaufman tests (2012, background): “Invariant first- and second-order loadings allowed for valid quantitative comparisons of factor variances and covariances across the age groups (Gregorich, 2006).”
Evaluating Measurement Invariance of TALIS 2013 Complex Scales: Comparison between Continuous and Categorical Multiple-Group Confirmatory Factor Analyses (2014, background): “Metric level of invariance is considered the minimum level of invariance if making comparisons of the relationship between factors across countries and observed variables (Byrne, 2008; Gregorich, 2006).”
Edinburgh Handedness Inventory – Short Form: A revised version based on confirmatory factor analysis (2014, background): “…these factor loadings to differ between groups significantly improved the model fit and they did not test the equality of item intercepts or error variances, which are requirements for testing whether findings of group mean differences can be accounted for by measurement biases (Gregorich, 2006).”
Assessing statistical aspects of test fairness with structural equation modelling (2013, methodology): “in composite means and variances on the indicators are unbiased estimates of the corresponding differences in both factor means and variances (Gregorich, 2006).”
Multiple-Group Confirmatory Factor Analysis in R--A Tutorial in Measurement Invariance with Continuous and Ordinal Indicators. (2014, background): “These techniques are also widely-used in medicine where measurement invariance is seen as an important precursor for interpreting patient reported outcomes (Gregorich, 2006).”
The Basic Psychological Needs in Physical Education Scale (2011, background): “, regression parameters) between latent variables (Gregorich, 2006).”