Multilevel Structural Equation Modeling - Online Course

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.

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.

Basic familiarity with Mplus is highly desirable, but even novice Mplus coders should be able to follow the presentation and do the exercises.

If you’d like to familiarize yourself with Mplus basics before the seminar begins, we recommend reading through UCLA’s short guide here.

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.

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

The fee of $1,395 includes all course materials.

PayPal and all major credit cards are accepted.

Our Tax ID number is 26-4576270.