Confirmatory Factor Analysis

Confirmatory factor analysis (CFA) is a form of a structural equation model that allows the estimation of latent variable through reflective indicators. As opposed to exploratory factor analysis, which can be used to estimate an unrestricted measurement model where indicators are allowed to depend on all factors, confirmatory factor analysis is used to estimate a restricted measurement model, where indicators typically depend on only one factor. Running a CFA is the first step in running a structural regression model. This workshop will introduce the main concepts behind confirmatory factor analysis.  Fit indices and modification indices will be discussed as ways of checking and improving model fit respectively.  It would be advantageous to be familiar with the concepts mentioned in the Introduction to Path Analysis workshop.

The workshop will include examples from R, where the lavaan package will be utilized to estimate CFAs. Participants should install the most recent versions of both R and RStudio on their computers prior to the workshop. To download and install R, visit https://cran.r-project.org/ and to download and install RStudio, visit https://posit.co.