Multilevel Structural Equation Modeling
A 5-Day Seminar Taught by Kristopher Preacher, Ph.D.
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 2-day Multilevel Modeling: A Second Course.
On Day 1 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
On Day 2 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
On Days 3-5 we will 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
Days 3-5 will also involve small group exercises to get practice using Mplus to fit models and conduct power analyses and Monte Carlo studies. Informal homework assignments will be given on Days 1-4, and discussed the following morning.
Throughout the five-day 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.
Who should attend?
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.
Mplus will be used for all worked examples, but prior knowledge of Mplus is not essential. You are welcome and encouraged to bring your own laptop computer with Mplus installed (including the multilevel or combination add-on). However, this is not required. Participants will still benefit from the comprehensive set of slides and syntax that they can apply at home.
Location, Format, and materials
The course meets 9 a.m. to 5 p.m. on Monday, July 13 through Friday, July 17 at The Gleacher Center, The University of Chicago Booth School of Business, 450 North Cityfront Plaza Drive, Chicago, IL 60611.
Participants receive a bound manual containing detailed lecture notes (with equations and graphics), examples of computer printout, and many other useful features. This book frees participants from the distracting task of note taking.
Registration and Lodging
The fee of $1895.00 includes all seminar materials. The early registration fee of $1695.00 is available until June 15.
If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50).
Lodging Reservation Instructions
Room blocks have been reserved at the following nearby hotels. Due to several city-wide conferences taking place during this seminar, hotel availability is extremely limited. We recommend making travel arrangements as early as possible. Once the room block deadlines pass, we will be unable to assist with securing lodging.
River Hotel, 75 E Upper Wacker Dr, Chicago, IL 60601. Make a reservation online by clicking here or call 203-905-2100 and reference group code SH2020 before Friday, June 12 to reserve a room for a rate of $193 per night. Approximately 0.3 miles from the Gleacher Center.
Aloft, 243 East Ontario Street, Chicago, IL 60611. Make a reservation online by clicking here or by calling Marriott Reservations at (800) 228-9290 or (312) 429-6600 and identifying yourself as part of the Statistical Horizons, LLC group staying at the Aloft Chicago Mag Mile before Friday, June 12 to reserve a room for a rate of $199 per night. Approximately 0.4 miles from the Gleacher Center.
Fairfield Inn & Suites, 216 E Ontario Street, Chicago, IL 60611. Make a reservation online by clicking here or call 855-476-6661 and reference Statistical Horizons before Monday, June 15 to reserve a room for a rate of $209 per night. Approximately 0.4 miles from the Gleacher Center.
Courtyard, 165 E Ontario, Chicago IL 60611. Make a reservation online by clicking here before Monday, June 22 to reserve a room for a rate of $244 per night. Approximately 0.4 miles from the Gleacher Center.
W Lakeshore, 644 N Lake Shore Dr, Chicago, IL 60611. Make a reservation online by clicking here or call 888-627-9034 and identify yourself as part of the Statistical Horizons, LLC group staying at the W Chicago – Lakeshore before Monday, June 22 to reserve a room for a rate of $258 per night. Approximately 0.6 miles from the Gleacher Center.
Acme Hotel, 15 E Ohio Street, Chicago, IL 60611. Make a reservation by calling 312-894-0800 and reference Statistical Horizons before Monday, June 15 at 4 p.m. CST to reserve a room for a rate of $199 per night. Approximately 0.5 miles from the Gleacher Center.
Other nearby hotel options include:
Sheraton Grand Chicago, 301 E North Water St, Chicago, IL 60611
DoubleTree, 300 E Ohio St, Chicago, IL 60611
Inn of Chicago, 162 E Ohio St, Chicago, IL 60611
Comfort Suites, 320 N Michigan Ave, Chicago, IL 60601
Westin, 320 N Dearborn St, Chicago, IL 60654
Cambria Hotel & Suites, 32 W Randolph St., Chicago, IL, 60601
Hotel EMC2, 228 E Ontario St, Chicago, IL 60611
Room blocks have not been reserved at these additional hotels, so reservations should be made directly or via a travel website.
“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
“A broadly applicable workshop on a powerful, gold-standard approach in a constantly growing field (multilevel data analysis). Compared to older approaches (MLM), MSEM is always better.”
“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
“Dr. Preacher did an excellent job explaining complex statistical methods in an intuitive way. He provides excellent notes and many resources and examples of code. He is also quite patient when fielding questions and provides numerous “on the fly” examples that greatly augment the course. I look forward to applying what I learned to address new hypotheses that before the course, I would not have had a clue how to approach. In other words, 10/10 would recommend!”
Michael Murphy, Carnegie Mellon University
“The instructor (K. Preacher) was patient and diligent in answering questions from many different levels of expertise. In our Multilevel SEM course, a lot of valuable information was covered, and he spent time assisting my team with developing a model for our specific project. Course content was taught thoughtfully. Some content was more advanced, so I would recommend strongly that future participants take introductory courses in Mplus and regression and various analytical methods prior to this course. Overall, an excellent opportunity with a very impressive expert!”
Lily Jiang, Indiana University