COVID-19 UPDATE: The safety of our students and staff is our top priority. Therefore, Stats Camp will be holding seminars online via live interactive zoom discussion groups. Our goal is to expand on the interactivity side and provide one-on-one consulting time via virtual breakout rooms. We are offering a discount code to a future camp worth $200 off and we are offering 1-hour of post camp consultation as an added value. Registrations will be accepted up to 12 hours prior to seminar start date and time. All seminars will be conducted in CDT time and will be recorded. The recordings will be made available to you within 3-5 business days of the live recording date. Access will be granted to the recorded videos for 1 year from the date of the seminar. Have questions? Contact us

Advanced Structural Equation Modeling: Bayesian SEM Seminar

Session 2: June 8 – 12, 2020
Albuquerque, NM – Embassy Suites


FAQVenue Info – Hotel Booking
$1,895 Faculty/Professional or $1,145 Student/Post-Doc

Payment Options

Seminar fee includes all materials, downloads, software access, training, refreshments and access to a recorded video of seminar:

Enrollment is open to public, students, graduates and professionals. Save a seat today, pay later.

Seminar Syllabus

Summer Stats Camp 2020: Bayesian SEM
MondayJune 8, 2020
9:00–10:45Welcome and Introductions.
10:45–11:00Snack and Refreshment Break.
11:00–12:30Bayesian reasoning and Baye’s rule : Direct probability vs indirect probability
12:30–1:30Lunch Break.
1:30–3:15Markov Chain Monte Carlo Estimation: Gibbs and Hamiltonian samplers
3:15–3:30Snack and Refreshment Break.
3:30–5:00Introduction to R: blavaan, JAGS, STAN
5:30~7:30Social “hour” for all Stats Campers
Tuesday June 9, 2020
9:00–10:45Know your distributions
10:45–11:00Snack and Refreshment Break.
11:00–12:30Confirmatory Factor Analysis
12:30–1:30Lunch Break.
1:30–3:15Priors: relevance, choice, strengths. CFA with cross-loadings
3:15–3:30Snack and Refreshment Break
3:30–5:00Individual Consultations
WednesdayJune 10, 2020
9:00–10:45Model fit and model comparison
10:45–11:00Snack and Refreshment Break
11:00–12:30Multiple-group CFA
12:30–1:30Lunch Break
1:30–3:15Latent regression models: latent interactions, quadratric effects, mediation
3:15–3:30Snack and Refreshment Break
3:30–5:00Individual Consultations.
ThursdayJune 11, 2020
9:00–10:45Robust SEM: non-normal continuous data
10:45–11:00Snack and Refreshment Break
11:00–12:30SEM for categorical data: Item Response Theory
12:30–1:30Lunch Break
1:30–3:15Missing data handling
3:15–3:30Snack and Refreshment Break
3:30–5:00Individual Consultations.
FridayJune 12, 2020
9:00–10:45Latent Growth Curve models
10:45–11:00Snack and Refreshment Break
11:00–12:30Multilevel SEM
12:30–1:30Lunch Break.
1:30~3:30Individual Consultations.

Why Should You Attend?

  • Get 1 on 1 Consultation With Instructor
  • Professional Networking
  • Peer Socializing
  • Collaboration
  • All Seminar Resources
  • Breakfast (Embassy guests), Lunches, & Snacks Daily

Statistical Methods Seminar Description

You have a good to great understanding of structural equation modeling (SEM), maybe you have been doing traditional SEM for years, but you’ve began a project where your observations are not normally distributed, you have a small sample size, or even worse – your model is not converging! What do you do now? Bayesian SEM is your next step!

Advanced SEM: Bayesian SEM will cover models that may be too complicated or impossible to estimate in the traditional SEM framework. This seminar highlights the philosophical and practical advantages of the Bayesian approach to SEM.

Overview: The goal of the Bayesian SEM is to provide instruction in the application SEM from the Bayesian paradigm. It will cover the application of models commonly implemented in frequentist SEM, and in models that are complicate or impossible to estimate in the frequentist paradigm. This seminar is design to portray the advantages of the Bayesian paradigm, both philosophical and practical, within the application of SEM. The material and examples will be provided in the open source platform R, but if the students prefer to work with another program we will assist in the understanding and application. In addition, students who sign up for this seminar can request topics to be included during the weeklong seminar. If we have the expertise, we’ll gladly prepare and deliver a module on the topic! As with all Stats Camp seminars, personal consultation time is available and ample support resources are provided on our web pages at statscamp.org.

A perfect follow up for SEM Foundations or Bayesian Data Analysis!

Instructor: Mauricio Garnier-Villarreal Ph.D.

Mauricio is a full time professor at Marquette. His Ph.D focus of Quantitative Psychology at the University of Kansas completed in the summer of 2016. His research focus is on the application of Bayesian methods to complex structure data for longitudinal analysis, from both mixed-effects and SEM models. He has experience not only working in the test and development of methods, but also in the application of these in data; in different fields like special education, cognitive decline in aging, healthy aging. He has been involved in the Stats Camp since 2011.

Seminar Files

Below are links to seminar files for those who enrolled in the seminar. Please download these files onto your computer before the first day of the seminar. The files are password protected to respect the intellectual property rights of the instructors. By using your login information you agree not to share your login information or the content protected by it.

Instructor will provide password on first day of seminar:
Click here to access the Advanced SEM Seminar Files

FAQs – Ask a Question About This Seminar

Q: Does this seminar focus on JAGS or STAN?

A: I do cover Stan. The seminar doesn’t focus on writing either JAGS or Stan code, since this is more complicated.

The seminar software focus on the use of blavaan (user friendly), which runs the analysis for you in either JAGS or Stan (your choice). For special cases of models, we go over how to edit the code (JAGS or Stan) to run models that blavaan doesnt include yet.

If there is the interest from a student to go over more detail Stan code we can do that, there is time to adjust the seminar to the students needs, or work on that during consultation.

Bayesian SEM Statistics Course