Confirmatory Factor Analysis
When we perform an Exploratory Factor Analysis (EFA), we’re not sure how many factors exist (if they exist at all) or what the factors represent. But when we hypothesize the existence of a certain number factors and how they manifest themselves through observable variables, we turn to Confirmatory Factor Analysis, or CFA, to test our hypothesis. In this workshop we introduce the basics of performing a CFA using the R statistical programming environment. Using the laavan and semPlot packages, we cover how to specify CFA models, how to interpret the output, how to evaluate fit, and how to create path diagrams summarizing our results. Prerequisites: Basic understanding of Exploratory Factor Analysis. Might also be helpful to know how to open a R script in RStudio and submit R code, though we’ll demonstrate that in the workshop.
Instructor: Clay Ford
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