Teacher’s Corner: Testing Measurement Invariance of Second-Order Factor Models. Structural Equation Modeling: A Multidisciplinary

We illustrate testing measurement invariance in a second-order factor model using a quality of life dataset (n = 924). Measurement invariance was tested across 2 groups at a set of hierarchically structured levels: (a) configural invariance, (b) first-order factor loadings, (c) second-order factor loadings, (d) intercepts of measured vari-ables, (e) intercepts of first-order factors, (f) disturbances of first-order factors, and (g) residual variances of observed variables. Given that measurement invariance at the factor loading and intercept levels was achieved, the latent factor mean difference on the higher order factor between the groups was also estimated. The analyses were performed on the mean and covariance structures within the framework of the con-firmatory factor analysis using the LISREL 8.51 program. Implications of sec-ond-order factor models and measurement invariance in psychological research were discussed. Second-order factor models have been used in psychology over a wide variety of domains, including the Big Five personality structure (DeYoung, Peterson, & Hig