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Registration closes on June 5th

Due to COVID-19 Workshop will be administered through Zoom

Longitudinal SEM: Applications with individual and family data
Prior workshops


16th June

Pre-Workshop Tutorial on basic analysis in MPLUS
  • Data prep
  • Basic syntax
  • Introduction to latent variable models, regression models, and path models
17th June

Day 1:
  • Basic intro to SEM
  • Data prep for longitudinal SEM
  • Data analyses with two time points
  • Examining measurement equivalence across time
  • Introduction to growth curve modeling

18th June

Day 2:
  • Adding predictors to growth curves (time variant and invariant)
  • Dual growth curves
  • Growth mixture modeling

Learn and Do:
This worksho is a "Learn and Do" Workshop. The workshop includes time to set up, analyze, and interpret models using your own data.


Wednesday June 16, 2021

MPLUS Pre-Workshop Tutorial on basic analysis

Thursday June 17 and Friday June18, 2021

Longitudinal SEM Summer Workshop


The Workshop will be held virtually, through Zoom. After you register and pay for the workshop, you will be provided with a link and password to join the Zoom meeting where instruction will take place.


Virtual Attendance Registration (due to COVID-19, we will only have virtual attendance)

A video link will be shared so you can attend virtually. Questions can be submitted during the workshop via email, and this registration comes with a 15 minute consultation before the workshop and a 30 minute consultation after the workshop to help answer any remaining questions).

· $300 for two day workshop and pre-workshop tutorial

· $200 for two day workshop only

· $100 for pre-workshop tutorial only

Student registration is $100 less for each category ($200 for all 3 days, $100 for 2 days, and $50 for the pre-workshop plus tutorial)

Justin Dyer, PhD

W. Justin Dyer received his Ph.D. in Human and Community Development from the University of Illinois at Urbana-Champaign after which he was a Postdoctoral Fellow at Auburn University. Following this he joined the faculty in the BYU School of Family where he taught courses on family processes and statistical methodology. He became part of the Religious Education faculty in 2015 and currently teaches the Eternal Family course (Religion C 200). His research area includes fatherhood with a particular emphasis on fathers in stressful circumstances such as fathers of children with disabilities and incarcerated fathers. His research also includes faith development in youth and how family processes influence that development. He has also written on the importance of the male-female relationship from a societal and theological perspective.

Jeremy Yorgason, PhD

Jeremy B. Yorgason is a Professor in the School of Family Life, and Director of the Gerontology Program at Brigham Young University. He received his PhD from Virginia Tech in marriage and family therapy. He also completed a graduate gerontology certificate at Kansas State University, and was a post-doctoral fellow at the Gerontology Center of Penn State University, with an emphasis in mental health and aging. Dr. Yorgason's research interests are in the area of later life family relationships, with a specific focus on health and marriage. Dr. Yorgason has taught structural equation modeling and other advanced applied statistics to graduate students for over ten years, and has used these techniques in several published papers. He and Dr. Dyer have taught the Longitudinal, Family SEM Workshop for several years.

What to Come Prepared With

Come prepared with your own computer with data processing software (SPSS or Stata or SAS, or other data processing software) and SEM software (MPlus or Amos or Stata, or other SEM software) installed.

Please have your own data to analyze. We will provide data you can use for practice, but if you can bring your own data we will help you analyze it. It helps if you can "clean" your data prior to the workshop by creating scales you plan to use. In addition to whatever cleaning you do, please also:

(1) trim the data set to have 300 or fewer variables
(2) remove any “string” variables that have text in them
(3) set all of the missing data values to be the same value (for example, set all missing to equal -9999).

If you need help with any of these three steps, please contact one of the presenters.

This Workshop has been taught each summer since 2015

Some features of this workshop include:
  • Handout packet and Box folder with examples of models
  • Hands-on learning
  • Assistance with multiple stats programs
  • Multiple people to help with data during the workshop
  • Layout of the workshop - time to listen, time to work with own data

"The presenters are able to take complex analyses and methods and explain them in simple everyday terms that make sense."

"The workshop was a great opportunity to learn how to analyze my own data with the guidance of professionals."


Registration closes on June 5th

Due to COVID-19 Workshop will be administered through Zoom