Multilevel Structural Equation Modeling

A 2-Week Remote Seminar Taught by
Kristopher Preacher, Ph.D.

Read reviews of this course

To see a sample of the course materials, click here.


Hierarchically clustered (multilevel or nested) data are common in the social sciences, medical fields, and business research. Clustered data violate the assumption of independence required by ordinary statistical methods. Increasingly complex research designs and hypotheses have created a need for sophisticated methods that go beyond standard multilevel modeling (MLM).

This course will introduce a variety of extensions to MLM, including cutting-edge multilevel structural equation modeling (MSEM) to handle complex designs and modeling objectives. Throughout the workshop, empirical examples will be presented to illustrate key concepts. A strong background in structural equation modeling (SEM) is not necessary.

Please note, this course will include all material from the on-demand seminar Multilevel Modeling: A Second Course

Starting June 16, we are offering this seminar over 6-days as a synchronous*, remote workshop for the first time. Live lectures will be held on Wednesday-Friday each week via the free video-conferencing software Zoom. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.

Lecture sessions will conclude with a hands-on exercise reviewing the content covered, to be completed on your own. An additional lab session will be held Wednesday and Thursday afternoons each week, where you can review the exercise results with the instructor and ask any questions.

*We understand that scheduling is difficult during this unpredictable time. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for two weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.


MORE DETAILS ABOUT THE COURSE CONTENT

We will begin by reviewing the basics of MLM. Next, Mplus will be introduced as a flexible and powerful software environment for fitting basic and advanced multilevel models. Then we will cover several advanced MLM topics.

Basic MLM topics include:

  • The motivation for MLM
  • Key concepts
  • Equation conventions
  • The univariate two-level MLM with fixed and random coefficients

Advanced MLM topics include:

  • Conducting power analysis for MLM using a general Monte Carlo technique
  • Fitting multivariate multilevel models
  • Modeling cross-classified data

Next, multilevel structural equation modeling will be introduced as a general approach for more complex modeling tasks. After a brief overview of single-level SEM, we will turn to the development of MSEM and the important advantages of MSEM over MLM (e.g., inclusion of latent variables, complex causal pathways, upper-level outcomes, and model fit assessment). Standard SEM and MLM will be recast as special cases of MSEM. Next we will cover a variety of MSEM topics:

  • Multilevel path analysis
  • Multilevel exploratory and confirmatory factor analysis
  • Model fit in MSEM

We will then continue to explore special applications of MSEM. Advanced topics will include:

  • Multilevel structural models with latent variables
  • Applications to three-level (and higher-level) data
  • Multilevel reliability estimation
  • Multilevel mediation analysis
  • Multiple group models
  • Estimating, plotting, and probing interaction effects
  • Moderation in MLM and MSEM
  • Modeling discrete (e.g., binary, count) dependent variables
  • Interval estimates for nonnormal statistics
  • Handling convergence problems: A bag of tricks
  • Conducting Monte Carlo simulation studies

Throughout the course, models will be presented in several formats—path diagrams, equations, and software syntax. Data and Mplus syntax for all of the examples will be included in the workshop materials.

Participants in this seminar can expect to gain:

  • Mastery of advanced topics in MLM
  • A deeper understanding of the relationship between MLM and SEM
  • The ability to use multilevel SEM to test complex structural hypotheses
  • Resources to conduct power analysis for virtually any multilevel design
  • The ability to fluently interpret and translate among path diagrams, model equations, and Mplus syntax for advanced MLM and MSEM
  • Strategies for tackling convergence problems and estimation errors
  • Programming skills for conducting Monte Carlo studies to assess model feasibility prior to data collection.
  • Documented Mplus syntax templates for fitting a variety of models to multilevel data.

COMPUTING

Mplus will be used for all worked examples, but prior knowledge of Mplus is not essential. You are welcome and encouraged to use a computer with Mplus installed (including either the multilevel or combination add-on). However, this is not required. You will still benefit from the comprehensive set of slides and syntax that you can apply at a later time.


WHO SHOULD Register? 

This seminar is designed for researchers who have had some exposure to multilevel modeling and/or structural equation modeling (e.g., from seminars, workshops, or courses) and who want to deepen and extend their knowledge.

At a minimum, participants should have a good working knowledge of basic principles of statistical inference (e.g., standard errors, hypothesis tests, confidence intervals), and should also have a good understanding of the theory and practice of linear regression.


SEMINAR OUTLINE

Day 1

  • Introduction
  • Review of MLM
  • Orientation to Mplus for MLM
  • Univariate MLM in Mplus
  • Multivariate MLM
  • Cross-classified data  

Day 2

  • Modeling discrete DVs
  • Overview of single-level SEM
  • Orientation to Mplus for SEM
  • SEM examples in Mplus
  • Introduction to multilevel SEM 

Day 3

  • MSEM equations and path diagrams
  • Orientation to Mplus for MSEM
  • SEM and MLM as special cases of MSEM
  • Multilevel path analysis
  • Multilevel confirmatory factor analysis
  • Model fit in MSEM
  • Multilevel exploratory factor analysis
  • General multilevel SEM with latent variables

Day 4

  • 3-level models in MLM vs. MSEM
  • Multilevel reliability estimation
  • Mediation in MLM and MSEM

Day 5

  • Multiple group multilevel models
  • Estimating, plotting, and probing interactions
  • Moderation in MSEM

Day 6

  • Interval estimates for nonnormal statistics
  • Handling convergence problems: A bag of tricks
  • Power analysis for MLM
  • Running Monte Carlo simulation studies

REVIEWS OF Multilevel Structural Equation Modeling

“I loved the MSEM course by Kris Preacher. The review at the start was a good refresher, but moved quickly into new concepts specific to MSEM. I really appreciated the code provided, the time left for questions, the practical applications, and covering logistical issues like convergence. It was a great course, and I feel prepared to use my new skills right away.”
  Abby Braitman, Old Dominion University

“Kris is a thoughtful and patient instructor. He fields questions easily and provides multiple examples pairing diagrams with equations with code and output.”
  Hayley Treloar Padovano, Brown University

“I came to this workshop with strong backgrounds in both MLM and SEM, but limited knowledge of MSEM. After reading a variety of papers prior to the course, I arrived with a long list of questions. At the end of the week, I am pleased to say that Kris answered each and every one of them. We covered a wide range of fundamental topics in MSEM, and I feel extremely confident in moving forward using these analyses in my own work. Kris is an excellent teacher and went above and beyond to make himself available to patiently answer everyone’s questions and help people with their own research. I would enthusiastically recommend this course (and Kris’s teaching in general) to students with SEM and MLM experience hoping to learn how to merge those methods!”
  Timothy Hayes, Florida International University

“The MSEM course was extremely helpful in fostering my statistical knowledge. I came into the course as a bit of a beginner, but Kris conveyed the material effectively to the variety of skill levels present in the classroom. I found the one-on-one consultation portion the most helpful, as I was allowed the opportunity to address my remaining questions from the material, along with my own statistical questions in my research. I would recommend the course to anyone looking to obtain a better understanding of MLM. I’m walking out of the course much better prepared in my statistical analyses.”
  Claire Tomlinson, Indiana University