期刊
PSYCHOLOGICAL METHODS
卷 10, 期 3, 页码 305-316出版社
AMER PSYCHOLOGICAL ASSOC
DOI: 10.1037/1082-989X.10.3.305
关键词
measurement; invariance; nonlinear; factor analysis; structural equation modeling
Measurement invariance is a necessary condition for the evaluation of factor mean differences over groups or time. This article considers the potential problems that can arise for tests of measurement invariance when the true factor-to-indicator relationship is nonlinear (quadratic) and invariant but the linear factor model is nevertheless applied. The factor loadings and indicator intercepts of the linear model will diverge across groups as the factor mean difference increases. Power analyses show that even apparently small quadratic effects can result in rejection of measurement invariance at moderate sample sizes when the factor mean difference is medium to large. Recommendations include the identification of nonlinear relationships using diagnostic plots and consideration of newly developed methods for fitting nonlinear factor models.
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