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A Short Course on Structural Equation Modeling

The registration is closed (event is full)

June 25 - June 27th, 2018
Mann Library B30A, Cornell University, Ithaca, NY
Early Registration Fee: $400.00 (until April 30th)
Regular Registration Fee: $475.00 (after April 30th)

Files: Data Files

Workshop Overview

Structural equation modeling (SEM) is a statistical methodology that is gaining popularity with researchers from a broad range of fields including sociology, psychology, clinical sciences, ecology, and biology. SEM provides a general framework for examining complex relationships between variables that may be either observed (manifest) or unobserved (latent). SEM can be used to investigate direct and indirect effects, handle correlated independent variables, and analyze longitudinal data. Path analysis and linear models are both special cases of SEMs.

This course will cover the fundamental theory behind SEM and provide attendees with the knowledge and skills necessary to confidently apply these methods to their own research. No previous background in SEM is necessary. Researchers from all fields are welcome. Additionally, every participant will have the opportunity during the course to consult with CSCU staff statisticians regarding their own research projects.

Specific topics to be covered include:

  • Overview of SEM methods
  • Review of linear models
  • Path analysis
  • Direct and indirect effects
  • Exploratory factor analysis
  • Confirmatory factor analysis
  • Reliability and validity
  • Regression with latent variables
  • Goodness of fit measures
  • Handling missing data via SEM
  • Generalized structural equation modeling
  • Latent growth curve models

Statistical Software

This course will have a substantial hands-on component using R via RStudio. Participants should have a working knowledge of both R and RStudio (e.g., be comfortable importing and manipulating data, performing simple statistical analyses, and fitting linear regression models). Participants will also be given an opportunity to register for a webinar on estimating linear models in R free of charge. Stata code for all hands-on components will also be provided for interested participants. All sessions will be held in a computer lab with PCs that have the most recent versions of R and RStudio installed, as well as Stata. You are also welcome to bring your own laptop to use during the course, but please make sure that you have the most recent version of both R and RStudio already installed. To download and install R, visit and to download and install RStudio, visit

Registration. (The registration is closed because the event is full)

The fee of $475.00 includes all seminar materials. An early registration fee of $400.00 is available until April 30th. Refunds cannot be provided for cancellations. Meals will not be provided (there will be a 1-hour lunch break each day), but drinks and a small snack will be provided during course breaks.


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If you have any questions about this short-course, please contact us at