This chapter presents basics of factor analysis modeling, focusing on its use and interpretations in scale and test development contexts. Two approaches to such analyses are discussed: exploratory factor analysis (EFA), in which one explores what factor structure the data represent; and confirmatory factor analysis (CFA), where one attempts to confirm a hypothesized factor structure. Text and illustrations demonstrate how one can use factor analysis results for deciding which items should be retained or deleted from a scale or test instrument. Model fit evaluation is discussed through the chi-square statistic, as well as some fit indices and information criteria. Uses of a CFA with covariates (MIMIC) and multiple-group CFA approaches for measurement invariance studies are also demonstrated. Lastly, basics of item response theory (IRT) modeling are introduced by demonstrating its parameter estimation and interpretations.
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