Use of Confirmatory Factor Analysis with Multiple Groups
This chapter focuses on using multiple-group confirmatory factor analysis (CFA) to examine the appropriateness of CFA models across different groups and populations. Multiple-group CFA involves simultaneous CFAs in two or more groups, using separate variance-covariance matrices (or raw data) for each group. Measurement invariance is be tested by placing equality constraints on parameters in the groups. Two examples of multiple-group CFA from the social work literature are discussed, and then a detailed multiple-group CFA building on the Job Satisfaction Scale (JSS) example presented in the previous chapter is presented. This is one of the more complex uses of CFA, and this chapter briefly introduces this topic; other resources are provided at the end of the chapter for more information.
Keywords: multiple-group CFA, variance-covariance matrices, raw data, job satisfaction scale, equality constraints, measurement invariance
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