Online Workshop: Structural Equation Modeling

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Structural Equation Modeling is one of the most popular and flexible modeling approaches in the social and health sciences.sem

It encompasses a number of models and processes you’ve used or heard of.  Models like linear regression, growth curve modeling, confirmatory factor analysis, mediation models, path analysis, and many more.

The problem, of course, with powerful and flexible statistical methods is also what makes them so great: there are so many options and seemingly small details with big impacts.

If you find you’ve been blindly following instructions to run models then gotten frustrated when models don’t converge, don’t fit, or you don’t know how to run the model you need, you’re in the right place.

This workshop will give you an intuitive understanding of the theory and philosophy behind SEM as well as the skills to implement it to specific types of models.

After the workshop, you’ll have a clear understanding of SEM, the skills to prepare data, run a SEM analysis, troubleshoot problems, and interpret estimates and fit indices.

And you’ll walk away with a set of ready-to-use syntax to run common SEM application in Mplus and R.

Every Live Workshop at The Analysis Factor includes:

✅ 1 year of access to the workshop website
✅ All the data, programming code, exercises and handouts you’ll need
✅ Live webinars and question & answer sessions
✅ Video recordings of all live content for later or repeated review
✅ The opportunity to ask questions live and on workshop web pages



In this Workshop, you will learn:

Session 1: Introduction and Review of Concepts

In this session, we’ll begin with a brief review of linear models and show how they are the building blocks of SEM.

We’ll then go through many of the new concepts, terminology, and notation used in SEM so that you have a strong base.

  • General linear model
  • Variance and covariance
  • Latent vs. observed variables
  • Endogenous and exogenous variables
  • Measurement vs. structural models
  • Path diagrams
    • Regression vs path analysis
  • Goodness of fit

Session 2: Observed variables only models

Next, we’ll move on to models that use observed variables.  These path models allow us to test both simple and sophisticated mediation.

  • Model specification
  • Revisiting multiple regression
  • Path Analysis: SEM without latent variables
    • Path Analysis
    • Mediation
    • Moderation in path models
    • Mediated moderation and moderated mediation
  • Options to plot path diagrams

Session 3: Measurement models with latent variables

In this session, we’ll dig into measurement models–models that measure latent variables with multiple observed variables.

  • Confirmatory Factor Analysis
    • Indicators as items
    • Basics of scale construction
    • Exploratory vs. Confirmatory Factor Analysis
    • Standardized vs. unstandardized coefficients
  • Data reduction and causality
    • Causal vs effect indicators

Session 4: Structural models with latent variables

Now we put path models and measurement models together to add a tremendous amount of flexibility in what we can test.

In this session you’ll learn the options, challenges, and solutions to fitting more complicated models.

  • Improving fit
    • Specification, misspecification, and re-specification
    • Modification indices
  • Exogenous and endogenous variables
  • Multigroup SEM

Session 5: Latent Curve Growth Models for Longitudinal Data

One particular type of SEM allows us to test longitudinal effects–the latent growth curve model.  This is very related to the random slope model in multilevel modeling and you’ll learn in detail how these random effects can be tested as latent variables in the SEM framework.

  • Model specification
  • Linear and quadratic slopes

Session 6: Advanced applications

And finally, we’ll introduce specific types of models that are extremely useful in very specific situations and how they fit into the SEM framework.

  • Exploratory Structural Equation Modeling (ESEM)
  • Mixture models
    • Latent Class Analysis
    • Growth Mixture Modeling
  • Binary and categorical variables
  • Item Response Theory


Who is it for?

This workshop is for you if you:

  • are an applied researcher with quantitative data and need to apply confirmatory factor analysis, mediation, or some other structural equation model
  • have attempted to learn structural equation modeling on your own and don’t feel comfortable with your current understanding of all the options
  • advise students who are using SEM in their research and need to improve your own understanding

It is not for you if you:

  • Are already an advanced user of latent variable modeling with extensive experience in SEM
  • work only on data sets without measurement error issues or not many variables of interest
  • Are a beginner in statistics and don’t have a solid background in linear regression


  • Understanding of and experience with linear models (ANOVA, multiple regression) is essential
  • Any exposure to R and/or Mplus OR openness to learning coding for new software. (If you have SAS, Stata, AMOS, Lisrel or some other software that can do SEM and are comfortable enough running things on your own, this workshop could still be useful. There will not be demonstrations in these, but the main focus is on concepts, steps, and interpretation, which apply to any software).

The Instructor:


manolo-2bE. Manolo Romero Escobar is a Senior Psychometrician at Multi-Health Systems Inc (a psychological test publishing company) in Toronto.

Before starting as a psychometrician he worked extensively as a research and statistical consultant for faculty, students at York University and for a variety of clients including health researchers, imaging clinics, educational institutions, and the Ontario government.

He has extensive expertise in factor analytical and latent-trait methods of measurement, as well as applications of linear mixed effects to nested, longitudinal, unbalanced data.

Manolo is passionate about the implementation of technology as an educational, learning, and training tool. He is an Excel, SPSS, and Mplus power user, and a supporter of the expanding use of the R language and environment for statistical computing.

Specialties: Linear Mixed Effects Modeling (HLM), Latent Variable Modeling (CFA, SEM), Scale Development (EFA, CFA, IRT, reliability, validity), Longitudinal Data Analysis.


The Workshop Format:

Our workshops have 3 main components that work together to support your learning.

1. Live Webinar Presentations of Workshop material, with recordings

Manolo will teach the workshop live via webinar. You attend over the internet, and you will see what is happening on his screen. Audio is through either your computer speakers/microphone or by telephone.

You can ask questions via phone or mic or via written chat, and you never have to leave your house or office.

Need to miss one or all sessions?  No problem.  You’ll get all the recordings.

2. Live Q&A Sessions, with recordings

After you’ve had about a week to work through all the materials, you have the opportunity to meet Manolo in three live Question & Answer sessions.

Bring your questions about the presentation or applying SEM to your own research.

3. Private workshop site with supplementary materials, resources, and Q&A

This private website is your home base for the workshop. It’s where you’ll find everything you need to support your learning:

Video recordings of every session

made available within 48 hours. Review the material right away, months later, or while doing the exercises. Or if you need to miss one (or all!) of the live sessions, you can still participate on your own schedule.

Data files

You get full access to use the data to try everything on your own.

Handouts including all the Mplus and R code

so you can replicate workshop examples on your own.  Keep and edit them for future projects.


(Yes, homework!). You really need to practice this stuff. Get your hands dirty.  And yes, we also give you the answers so you can check your work.

A place to submit written questions between sessions

So as you’re reviewing videos afterward (or if you missed a live session), just submit a question. Manolo will answer it right there on the website.

Bonus videos on related topics

  • Matrix Algebra for Data Analysts: A Primer
  • Mediation
  • Introduction to Structural Equation Modeling
  • Mixture Models in Longitudinal Data Analysis
  • Latent Class Analysis
  • Exploratory Factor Analysis

You’ll have access for a year to the workshop website.

So as we add resources, re-record sessions, and answer more questions each time we offer the workshop, you have access to the updated material.

What Our Students Say About Our Workshops:


“I regularly take ecourses and like that format, but this is a step better because there are real time webinars and Q&A sessions that permit you to have a recorded version of your particular question getting answered. The pacing was great even though I didn’t fully soak up everything and the instructor was extremely well prepared, polite and responsive to questions and comments. Can’t ask for more.”

David Fabienke, MPP

“The ability to hang on to all of these materials, including the bonus materials is a really great feature. I feel like I have this whole library of references that I can go back to if I need it.”

Noelle Chesley

“The materials, technology, organization, and topic selection are all excellent; a model of online instruction. I specifically appreciated the opportunity for the live Q&A, although wasn¹t always able to take advantage of it. For that reason, the recordings were also very helpful.”

Jason Hurwitz, PhD Assistant Research Scientist, University of Arizona

“Thank you so much. I learned so much in this workshop and it will change the way I examine (and design) my data sets from now on! I think the homework is an excellent part of the workshop. The video recordings are terrific. All of the resources provided for this workshop were outstanding.”

Prudence Plummer-D’Amato, PhD

“The Q&As were Š helpful because you could hear real-life examples others were working on, from different angles. Helps to reinforce the concepts.”

J. Basta, PhD Program Evaluation & Research Consultant

“It was a very thorough set of workshops, a good pace, and it should prove to be an asset to my future data analysis projects.”

David Scott



Full Workshop Investment: $397

We’re sorry but this workshop is not currently enrolling.
Please join our waiting list to receive a notification when it is offered again.


Refund Policy: Your registration fee is fully refundable up to 72 hours in advance. Because enrollment is limited, no refunds will be granted after the program begins.


As with all our programs, your satisfaction is guaranteed. If you participate fully in this workshop–watch, read, and try out everything included–and find you are not satisfied for any reason, we will give you a full refund, no questions asked.

Just notify us within 90 days of purchasing the program.