Improving measurement invariance assessments in survey research with missing data by novel artificial neural networks

Gender Differences in Factors Affecting Science Performance of Eighth Grade Taiwan Students

“…In order to test whether the multiple-group analysis was valid and equivalent across gender statistically, gender invariance was tested through a series of nested models with the establishment of successive equivalence constraints in the model parameters across groups (Byrne 2008;Byrne and Stewart 2006;Cheung and Rensvold 2002;Tsai and Yang 2012). Configural invariance (Model 1) was the first level, also called baseline model, which had the least number of restricted parameters.…”

“…If models with more constrained parameters yield a good model-data fit, we have greater confidence that the hypothesized model is stable and valid for Taiwanese eighth grade students. In other words, invariance of the hypothesized model across gender frequently reflected invariance of relations among observed and latent variables in the model (Chen et al 2011;Tsai and Yang 2012).…”

Development of Marine Science Affect Scale for Junior High School Students in Taiwan: Testing for Measurement Invariance

“…Confirmatory factor analysis (CFA) was also used in this study to evaluate construct validity. A series of multigroup CFA (MGCFA) analyses using Mplus 7 (Muthén & Muthén, 1998, based on the MLR (maximum likelihood estimation with robust standard errors) estimation procedure (Muthén & Muthén, 1998Tsai & Yang, 2012Tsai, Yang, & Chang, 2015) for conducting measurement invariance across gender, were also conducted.…”

“…To test whether the multiple-group analysis is valid and the invariance equivalent statistically, measurement invariance was tested through a series of nested models detection processes across groups (Byrne, 2008;Byrne & Stewart, 2006;Cheung & Rensvold, 2002;Tsai & Yang, 2012;Tsai et al, 2015). The first level involved the configural invariance (Model 1), also called the baseline model, with the least restrictions of the parameters.…”

“…In addition to the reliability and validity of the development scale, measurement invariance must be established. Assessing measurement invariance is valuable when developing a measurement or questionnaire, especially in cross-cultural or group investigations, because it allows the researcher to determine whether participants from different groups or cultures attribute the same meanings to questionnaire items (Chen, 2008;Cheung & Rensvold, 2002;Cheung & Rensvold, 2000;Milfont & Fischer, 2010;Tsai, Yang, & Chang, 2015;Tsai & Yang, 2012). Measurement invariance does not mean that all subjects are equal with respect to the variable in question, rather that they are equal with respect to the instrument in question (Tsai et al, 2015).…”