TY - JOUR
T1 - Testing measurement invariance of second-order factor models
AU - Chen, Fang Fang
AU - Sousa, Karen H.
AU - West, Stephen
N1 - Funding Information:
This project was supported by a National Institute of Nursing Research grant (NR04817) to Karen H. Sousa. We particularly thank Roger Millsap for his insights on testing measurement invariance and comments on earlier versions of this article. We also thank Oi-Man Kwok for his assistance and his comments on an earlier version of this article. Fang Fang Chen is now at the Department of Psychology, University of Delaware.
PY - 2005
Y1 - 2005
N2 - 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 variables, (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 confirmatory factor analysis using the LISREL 8.51 program. Implications of second-order factor models and measurement invariance in psychological research were discussed.
AB - 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 variables, (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 confirmatory factor analysis using the LISREL 8.51 program. Implications of second-order factor models and measurement invariance in psychological research were discussed.
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U2 - 10.1207/s15328007sem1203_7
DO - 10.1207/s15328007sem1203_7
M3 - Review article
AN - SCOPUS:24944491841
SN - 1070-5511
VL - 12
SP - 471
EP - 492
JO - Structural Equation Modeling
JF - Structural Equation Modeling
IS - 3
ER -