Multilevel Modeling: A Second Course - Online Course
A 3-Day Livestream Seminar Taught by
Kristopher Preacher10:00am-12:30pm (convert to your local time) Thursday-Saturday
1:30pm-4:00pm Thursday, 1:30pm-3:30pm Friday & Saturday
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 “second course” in MLM will introduce a variety of MLM extensions, including cutting-edge multilevel structural equation modeling (MSEM) to handle complex designs and modeling objectives. Throughout the seminar, empirical examples will be presented to illustrate key concepts. A background in structural equation modeling (SEM) is not necessary.
Starting November 10, we are offering this seminar as a 3-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. 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.
*We understand that finding time to participate in livestream courses can be difficult. 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 four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.
Closed captioning is available for all live and recorded sessions.
More details about the course content
We will begin the seminar by reviewing the basics of MLM, including:
-
- The motivation for MLM
- Key concepts
- Equation conventions
- The univariate two-level MLM with fixed and random coefficients
Mplus will be introduced as a flexible and powerful software environment for fitting basic and advanced multilevel models. Next, we will cover several advanced MLM topics, including:
-
- Estimating, plotting, and probing interaction effects
- Modeling cross-classified data
- Modeling discrete (e.g., binary, count) dependent variables
- Conducting power analysis for MLM using a general Monte Carlo technique
- Fitting multivariate multilevel models
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 exploratory and confirmatory factor analysis
- Multilevel path analysis
- Multilevel structural models with latent variables
- Multilevel mediation analysis
- Multilevel reliability estimation
- Applications to cross-classified and three-level data
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
- Documented Mplus syntax templates for fitting a variety of multilevel models.
We will begin the seminar by reviewing the basics of MLM, including:
-
- The motivation for MLM
- Key concepts
- Equation conventions
- The univariate two-level MLM with fixed and random coefficients
Mplus will be introduced as a flexible and powerful software environment for fitting basic and advanced multilevel models. Next, we will cover several advanced MLM topics, including:
-
- Estimating, plotting, and probing interaction effects
- Modeling cross-classified data
- Modeling discrete (e.g., binary, count) dependent variables
- Conducting power analysis for MLM using a general Monte Carlo technique
- Fitting multivariate multilevel models
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 exploratory and confirmatory factor analysis
- Multilevel path analysis
- Multilevel structural models with latent variables
- Multilevel mediation analysis
- Multilevel reliability estimation
- Applications to cross-classified and three-level data
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
- Documented Mplus syntax templates for fitting a variety of multilevel models.
Computing
Mplus will be used for all worked examples. You are welcome and encouraged to use 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 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.
Mplus will be used for all worked examples. You are welcome and encouraged to use 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 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.
Who should register?
This seminar is designed for researchers who have some prior experience with multilevel modeling (e.g., in a seminar, workshop, or course) 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.
This seminar covers much of the same content as Kristopher Preacher’s 6-day livestream Multilevel Structural Equation Modeling seminar.
This seminar is designed for researchers who have some prior experience with multilevel modeling (e.g., in a seminar, workshop, or course) 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.
This seminar covers much of the same content as Kristopher Preacher’s 6-day livestream Multilevel Structural Equation Modeling seminar.
Seminar outline
Day 1
-
- Introduction
- Review of MLM
- Orientation to Mplus for MLM
- Univariate MLM in Mplus
- Overview of single-level SEM
- Orientation to Mplus for SEM
- SEM examples in Mplus
Day 2
-
- Introduction to multilevel SEM
- MSEM equations and path diagrams
- Orientation to Mplus for MSEM
- Multivariate MLM
- Multilevel path analysis
- Multilevel confirmatory factor analysis
- Model fit in MSEM
- Multilevel exploratory factor analysis
Day 3
-
- General multilevel SEM with latent variables
- Multiple group multilevel models
- Estimating, plotting, and probing interactions
- Moderation in MSEM
- Mediation in MLM and MSEM
- Power analysis for MLM
- Interval estimates for nonnormal statistics
Day 1
-
- Introduction
- Review of MLM
- Orientation to Mplus for MLM
- Univariate MLM in Mplus
- Overview of single-level SEM
- Orientation to Mplus for SEM
- SEM examples in Mplus
Day 2
-
- Introduction to multilevel SEM
- MSEM equations and path diagrams
- Orientation to Mplus for MSEM
- Multivariate MLM
- Multilevel path analysis
- Multilevel confirmatory factor analysis
- Model fit in MSEM
- Multilevel exploratory factor analysis
Day 3
-
- General multilevel SEM with latent variables
- Multiple group multilevel models
- Estimating, plotting, and probing interactions
- Moderation in MSEM
- Mediation in MLM and MSEM
- Power analysis for MLM
- Interval estimates for nonnormal statistics
Payment information
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.