Testing Measurement Invariance: A Comparison of Multiple-Group Categorical CFA and IRT

By E. S. Kim, Myeongsun Yoon. 2011

235 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/bf1ba596b768f69f1e291e6dbea75dd8b507a7c7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Taehun Lee
2. Rex Bryan Kline
3. Myeongsun Yoon
4. E. S. Kim
5. Eunju Jung

In Management Science and Operations Research

1. Taehun Lee
2. Rex Bryan Kline
3. Myeongsun Yoon
4. E. S. Kim
5. Eunju Jung
6. Luke Plonsky
7. F. Oswald
8. M. Şahin

In Statistics and Probability

1. E. S. Kim
2. Taehun Lee
3. Eunju Jung
4. Rex Bryan Kline
5. Myeongsun Yoon
6. D. Dimitrov

Citations in the corpus

• Assessing statistical aspects of test fairness with structural equation modelling (2013, background): “Indeed, estimation of model parameters in SEM assumes that the model is correctly specified, a very strong assumption not always fully appreciated in practice (Kline, 2012). Serious specification error in the analysis can prevent the researcher from discovering the “true” model. In MGCFA, it can hap”
• Comparisons of Three Empirical Methods for Partial Factorial Invariance: Forward, Backward, and Factor-Ratio Tests (2016, background): “Only recently have researchers begun to include in their simulation studies scalar invariance (Kim & Yoon, 2011; Kim, Yoon, & Lee, 2012).”
• Recent Methods for the Study of Measurement Invariance With Many Groups (2018, unknown): “yij = νj + λj fWij + ij, (22) νj = ν + λ fBj + νj , (23) λj = λ+ λ fψj + λj , (24)”
• Testing Measurement Invariance Using MIMIC (2012, methodology): “The parameter values, the magnitude of DIF, and sample size were selected with the reference to the previous simulation studies on the similar research conditions (Kim & Yoon, 2011; Meade & Lautenschlager, 2004; Muthén & Asparouhov, 2002; Stark et al., 2006; Yoon, 2008; Yoon & Millsap, 2007).”
• A Bayesian Approach to Multilevel Structural Equation Modeling With Continuous and Dichotomous Outcomes (2015, unknown): “Simplifying the measurement model in such a manner is practically useful because it allows for a straightforward interpretation of contextual effects as a simple decomposition of the between-group and within-group effects (Kim & Yoon, 2011; Mehta & Neale, 2005).”