Structural Equation Modeling

First Steps in Structural Equation Modeling: Confirmatory Factor Analysis

February 7th, 2020 by

Confirmatory factor analysis (CFA) is the fundamental first step in running most types of SEM models. You want to do this first to verify the measurement quality of any and all latent constructs you’re using in your structural equation model.

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Member Training: Reporting Structural Equation Modeling Results

October 1st, 2019 by

The last, and sometimes hardest, step for running any statistical model is writing up results.

As with most other steps, this one is a bit more complicated for structural equation models than it is for simpler models like linear regression.

Any good statistical report includes enough information that someone else could replicate your results with your data.

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Member Training: Latent Growth Curve Models

October 1st, 2018 by
What statistical model would you use for longitudinal data to analyze between-subject differences with within-subject change?

Most analysts would respond, “a mixed model,” but have you ever heard of latent growth curves? How about latent trajectories, latent curves, growth curves, or time paths, which are other names for the same approach?


To Moderate or to Mediate?

May 21st, 2018 by


We get many questions from clients who use the terms mediator and moderator interchangeably.

They are easy to confuse, yet mediation and moderation are two distinct terms that require distinct statistical approaches.

The key difference between the concepts can be compared to a case where a moderator lets you know when an association will occur while a mediator will inform you how or why it occurs.

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Member Training: Model Fit Statistics in Structural Equation Modeling

December 1st, 2017 by

Structural Equation Modelling (SEM) increasingly is a ‘must’ for researchers in the social sciences and business analytics. However, the issue of how consistent the theoretical model is with the data, known as model fit, is by no means agreed upon: There is an abundance of fit indices available – and wide disparity in agreement on which indices to report and what the cut-offs for various indices actually are. (more…)


What Are Nested Models?

July 28th, 2017 by

Pretty much all of the common statistical models we use, with the exception of OLS Linear Models, use Maximum Likelihood estimation.

This includes favorites like:

That’s a lot of models.

If you’ve ever learned any of these, you’ve heard that some of the statistics that compare model fit in competing models require (more…)