Confirmatory factor analysis (CFA) is a specific type of factor analysis that allows one to determine the extent of the hypothesized relationship between observed indicators and factors (underlying latent variables). CFA, unlike path analysis, allows the distinction between latent variables (referred to as factors) and the indicators (variables) used to measure these latent variables. With CFA models, the factors are assumed to cause the variation and covariation between the observed indicators which are fit to a correlation matrix. This assumption is the primary distinction between CFA and exploratory factor analysis models in which no hypothesis about the number of factors and the relationship between those factors and the indicators is proposed. Thus, CFA can be used for psychometric evaluation, construct validation, and testing measurement invariance. ...
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