This short course will introduce you to the major ideas behind structural equation modeling (SEM) and equip you with the knowledge necessary to get started on your own analysis using this method. SEM is a valuable tool beyond traditional regression models due to its flexibility, as it allows researchers to test more complex relationships among variables and to account for measurement error in analysis.

This course will cover the basics of:

• Confirmatory factor analysis
• Path analysis
• Structural equation models with latent variables
• Evaluating indirect relationships between variables
• Using fit statistics to test competing hypotheses
• Examples and exercises will use the R package lavaan, but content from this course will be directly applicable to other programs that estimate structural equation models, such as Mplus and Stata.

Participants should be familiar with regression modeling before taking this course. Experience using R will be helpful but is not required.