Structural Regression Models

Structural regression models allow researchers to do path analysis on latent variables. At its core, structural regression models have a measurement model, which is estimated using confirmatory factor analysis, and a structural part, which consists of hypotheses about the direct and indirect effects among observed or latent variables. Researchers often conflate the terms structural equation model (SEM) and structural regression (SR); it is important to keep in mind that SEM is an umbrella that contains path analysis, CFA, SR, as well as other techniques.

In this workshop, we will focus on the specification, identification, and interpretation of SR models. Fit indices and modification indices will also be discussed. It would be advantageous to be familiar with the concepts mentioned in the Introduction to Path Analysis  and Confirmatory Factor Analysis workshops.

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 and to download and install RStudio, visit