Detecting Violations of Factorial Invariance Using Data-Based Specification Searches: A Monte Carlo Study

By Myeongsun Yoon, R. Millsap. 2007

207 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/41994d63f487c8102f2d92d30ff5815157b81f07

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Citations in the corpus

Measurement Invariance for Latent Constructs in Multiple Populations (2012, methodology): “…and (b) group identity in mean intercepts (constraint [5]) when prior knowledge is available that amounts to group identity in the intercepts of a reference indicator per factor (cf. Millsap, 2011; Millsap & Olivera-Aguilar, in press; Vandenberg & Lance, 2000; Woods, 2009; Yoon & Millsap, 2007).”
Testing for Factorial Invariance in the Context of Construct Validation (2010, methodology): “…but it can be based, ideally, on sound theoretical considerations or recently developed procedures for selecting RIs (e.g., Rensvold & Cheung, 2001; Yoon & Millsap, 2007); the computations in the procedure proposed by Yoon and Millsap (2007) are less complicated than those in the procedure…”
Testing Measurement Invariance in Longitudinal Data with Ordered-Categorical Measures (2016, unknown): “…invariance model is rejected, and if the following examination of the modification indices reveals a constrained threshold with a high modification index, then constraining the equality of a different threshold over time should be considered for model identification (Yoon & Millsap, 2007).”
Getting to Know You (2017, unknown): “We examined the tau parameters of the metric invariance model and constructed 95% confidence intervals to identify items that functioned differentially across data waves and to minimize the risk of false detection (Yoon & Millsap, 2007).”
Using Modification Indexes to Detect Turning Points in Longitudinal Data: A Monte Carlo Study (2010, result): “Our findings were consistent with other studies in which MIs were used to detect potential misspecification in other SEM contexts involving searches of a highly restricted parameter space (e.g., structural equation models: MacCallum, 1986; factorial invariance: Yoon & Millsap, 2007).”
Testing Measurement Invariance: A Comparison of Multiple-Group Categorical CFA and IRT (2011, methodology): “There are several options for identification of an MCCFA model ( Reise et al, 1993 ; Yoon & Millsap, 2007 ): (a) marker variable strategy that assigns one item as a reference variable to render an appropriate scale to the factor scores, (b) factor variance strategy that fixes the factor variances o”
Evaluating Model Fit With Ordered Categorical Data Within a Measurement Invariance Framework: A Comparison of Estimators (2014, background): “…focused on several areas: (a) issues related to setting the measurement scale (Cheung & Rensvold, 1999; French & Finch, 2008; Raykov et al., 2013; Yoon & Millsap, 2007), (b) evaluating model fit (Chen, 2007; Cheung & Rensvold, 2002; Meade et al., 2008) and statistical power (French & Finch,…”
Testing Factorial Invariance in Multilevel Data: A Monte Carlo Study (2012, background): “Measurement invariance refers to the equivalent probability of an observed score in a test given the identical ability regardless of group membership of an observation ( Yoon & Millsap, 2007 ).”
Comparisons of Three Empirical Methods for Partial Factorial Invariance: Forward, Backward, and Factor-Ratio Tests (2016, methodology): “In addition, neither study examined scalar invariance to evaluate the performance of the factor-ratio test (French & Finch, 2008) or the backward MI method (Yoon & Millsap, 2007).”
Testing Factorial Invariance With Unbalanced Samples (2018, methodology): “…method, unbalanced sample sizes Measurement invariance is defined as a condition in which the conditional probability of measured scores given one’s standing on the latent construct being measured is independent of one’s group membership (Mellenbergh, 1989; Millsap, 2011; Yoon & Millsap, 2007).”
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 Direct Comparison Approach for Testing Measurement Invariance (2012, methodology): “Nevertheless, it should be noted that the MI method tends to have high Type I error and inadequate power (Yoon & Millsap, 2007).”