Structural Equation Modeling with Categorical Data - Online Course
A 4-Day Livestream Seminar Taught by
Wes BonifayTuesday, June 18 –
Friday, June 21, 2024
10:30am-12:30pm (convert to your local time)
1:30pm-3:00pm
Structural equation modeling (SEM) is a framework for fitting many types of statistical models, including simple regression models, multivariate path models, confirmatory factor models, latent variable path models, and latent growth models. Since its inception, the standard SEM specification has been a linear model with normally distributed outcomes, often considered “continuous.” That’s been a considerable limitation because many outcome variables are binary or ordinal, or considered “categorical,” in almost every discipline. Unfortunately, categorical models differ in several ways from standard SEM, and there are few didactic articles on how to properly use and interpret categorical SEM. This seminar will cover a wide range of topics within the categorical SEM framework.
Starting June 18, we are offering this seminar as a 4-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. Live captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.
More details about the course content
On Day 1, we will explore the foundational components of this framework, from logistic and probit regression models to the basic tenets of SEM. Day 2 will focus on measurement components through a detailed examination of confirmatory factor analysis of binary and ordinal indicators, including model specification, estimation methods, and software implementation.
Day 3 will highlight the structural components (e.g., regressions among variables), with an overview of path analysis and SEM with categorical data, accompanied by practical implementations. Lastly, Day 4 will involve advanced topics such as missing data handling, multigroup CFA/measurement invariance testing, and the integration of SEM with other frameworks (e.g., item response theory).
While many SEM software programs are still limited to linear/normal models, the last decade has seen the emergence of several SEM programs and packages that do an excellent job of estimating categorical models. Accordingly, this seminar will present a comprehensive treatment of SEM for binary and ordinal outcomes, using two of the best software packages for the task: Mplus and lavaan (a package for R).
On Day 1, we will explore the foundational components of this framework, from logistic and probit regression models to the basic tenets of SEM. Day 2 will focus on measurement components through a detailed examination of confirmatory factor analysis of binary and ordinal indicators, including model specification, estimation methods, and software implementation.
Day 3 will highlight the structural components (e.g., regressions among variables), with an overview of path analysis and SEM with categorical data, accompanied by practical implementations. Lastly, Day 4 will involve advanced topics such as missing data handling, multigroup CFA/measurement invariance testing, and the integration of SEM with other frameworks (e.g., item response theory).
While many SEM software programs are still limited to linear/normal models, the last decade has seen the emergence of several SEM programs and packages that do an excellent job of estimating categorical models. Accordingly, this seminar will present a comprehensive treatment of SEM for binary and ordinal outcomes, using two of the best software packages for the task: Mplus and lavaan (a package for R).
Computing
Empirical examples and exercises will be demonstrated using Mplus and R. To participate in the hands-on exercises, you should have a computer with Mplus and/or R installed. All analyses can be completed using Mplus, while many (but not all) can be completed using R. R users should also install RStudio, a freely available interface for R, and the lavaan package for SEM. The demo version of Mplus will suffice.
You should have good familiarity with the use of Mplus or R, including opening and executing data files and programs.
If you’d like to familiarize yourself with Mplus basics before the seminar begins, we recommend reading through UCLA’s short guide here.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent on-line resources for building your R skills.
Empirical examples and exercises will be demonstrated using Mplus and R. To participate in the hands-on exercises, you should have a computer with Mplus and/or R installed. All analyses can be completed using Mplus, while many (but not all) can be completed using R. R users should also install RStudio, a freely available interface for R, and the lavaan package for SEM. The demo version of Mplus will suffice.
You should have good familiarity with the use of Mplus or R, including opening and executing data files and programs.
If you’d like to familiarize yourself with Mplus basics before the seminar begins, we recommend reading through UCLA’s short guide here.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent on-line resources for building your R skills.
Who should register?
If you want to learn how to apply structural equation models to binary and ordinal data and have a solid background in structural equation modeling, then this course is for you. You should have completed coursework up to and including multiple regression and the equivalent of a two-semester graduate-level sequence in statistics. Familiarity with factor analysis is helpful, but not required. No level of proficiency beyond basic awareness is assumed for mathematical or statistical topics.
Previous experience with R and/or Mplus would be helpful, but not required.
If you want to learn how to apply structural equation models to binary and ordinal data and have a solid background in structural equation modeling, then this course is for you. You should have completed coursework up to and including multiple regression and the equivalent of a two-semester graduate-level sequence in statistics. Familiarity with factor analysis is helpful, but not required. No level of proficiency beyond basic awareness is assumed for mathematical or statistical topics.
Previous experience with R and/or Mplus would be helpful, but not required.
Seminar outline
Day 1: Foundational Components
-
- Overview of categorical data analysis
- Introduction to R (lavaan) and Mplus syntax
- Logistic and probit regression models
- Implementation in R and Mplus
- Introduction to structural equation modeling
Day 2: Measurement Components
-
- Overview of factor analysis
- Confirmatory factor analysis with binary and ordinal indicators
- Model specification
- Matrix formulation
- Estimation methods
- Model evaluation methods
- Implementation in R and Mplus
Day 3: Structural Components
-
- Overview of path analysis
- Implementation in R and Mplus
- Structural equation modeling with categorical data
- Model specification
- Matrix formulation
- Estimation methods
- Model evaluation methods
- Implementation in R and Mplus
Day 4: Advanced Components
-
- Methods for handling missing data
- Multigroup CFA/measurement invariance testing
- Advanced applications (e.g., longitudinal data models, multiple informants model)
- Links between SEM and other frameworks (e.g., item response theory)
Day 1: Foundational Components
-
- Overview of categorical data analysis
- Introduction to R (lavaan) and Mplus syntax
- Logistic and probit regression models
- Implementation in R and Mplus
- Introduction to structural equation modeling
Day 2: Measurement Components
-
- Overview of factor analysis
- Confirmatory factor analysis with binary and ordinal indicators
- Model specification
- Matrix formulation
- Estimation methods
- Model evaluation methods
- Implementation in R and Mplus
Day 3: Structural Components
-
- Overview of path analysis
- Implementation in R and Mplus
- Structural equation modeling with categorical data
- Model specification
- Matrix formulation
- Estimation methods
- Model evaluation methods
- Implementation in R and Mplus
- Overview of path analysis
Day 4: Advanced Components
-
- Methods for handling missing data
- Multigroup CFA/measurement invariance testing
- Advanced applications (e.g., longitudinal data models, multiple informants model)
- Links between SEM and other frameworks (e.g., item response theory)
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.