Latent Class Analysis - Online Course
Thursday, February 23 –
Saturday, February 25, 2023
10:00am-12:30pm (convert to your local time)
1:30pm-3:30pm
Latent class analysis (LCA) is an intuitive and rigorous tool for uncovering hidden subgroups in a population. It can be viewed as a special kind of structural equation modeling in which the latent variables are categorical rather than continuous. This seminar will give you the theoretical background and applied skills to address interesting research questions using LCA. You will also be introduced to latent transition analysis (LTA), a longitudinal extension of LCA.
Other topics include model identification, model selection, model interpretation, multiple-groups LCA, measurement invariance across groups, and LCA with covariates and distal outcomes. The seminar will combine lectures, software demonstrations, computer exercises, and discussion. There will be opportunities to discuss how LCA and LTA can be applied in your own research.
Starting February 23, 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.
Computing
All examples and exercises will use SAS and the free add-on procedures PROC LCA and PROC LTA developed by Dr. Lanza and her colleagues. Coverage will include both basic and advanced features of PROC LCA, but only basic features of PROC LTA. If you prefer Mplus, Stata, or Latent Gold, you can get equivalent program code for these packages by request.
Basic familiarity with SAS is highly desirable, but even novice SAS users with access to the software and add-on procedures should be able to follow the presentation and do the exercises.
To complete the exercises, you will need your own computer with a recent version of SAS and the free add-on procedures, PROC LCA and PROC LTA, installed.
Note: PROC LCA and PROC LTA do not function with the free University Edition of SAS.
All examples and exercises will use SAS and the free add-on procedures PROC LCA and PROC LTA developed by Dr. Lanza and her colleagues. Coverage will include both basic and advanced features of PROC LCA, but only basic features of PROC LTA. If you prefer Mplus, Stata, or Latent Gold, you can get equivalent program code for these packages by request.
Basic familiarity with SAS is highly desirable, but even novice SAS users with access to the software and add-on procedures should be able to follow the presentation and do the exercises.
To complete the exercises, you will need your own computer with a recent version of SAS and the free add-on procedures, PROC LCA and PROC LTA, installed.
Note: PROC LCA and PROC LTA do not function with the free University Edition of SAS.
Who should register?
If you plan to analyze cross-sectional or longitudinal data and believe that there are meaningful subgroups of individuals characterized by the intersection of multiple characteristics, this seminar is for you. These subgroups might be defined by patterns of problem behavior, risk exposure, product preference, political alignment, and many other hard-to-measure constructs.
You should have a good working knowledge of the principles and practice of multiple regression; familiarity with logistic regression is helpful.
If you plan to analyze cross-sectional or longitudinal data and believe that there are meaningful subgroups of individuals characterized by the intersection of multiple characteristics, this seminar is for you. These subgroups might be defined by patterns of problem behavior, risk exposure, product preference, political alignment, and many other hard-to-measure constructs.
You should have a good working knowledge of the principles and practice of multiple regression; familiarity with logistic regression is helpful.
Seminar outline
Day 1: Introduction to latent class analysis (LCA)
- Conceptual introduction to LCA
- An example: latent classes of adolescent drinking behavior
- Parameters estimated in LCA
- Technical considerations: model identification, model selection
- Software options
Day 2: Adding features to “baseline” models
- Including a grouping variable
- Review of logistic regression
- Predicting latent class membership
- Predicting a distal outcome
- Conceptual introduction to latent profile analysis (LPA)
Day 3: Introduction to latent transition analysis (LTA)
- Conceptual introduction to LTA
- An example: latent classes of dating and sexual risk behavior
- Technical details
- Including a grouping variable
- Predicting transitions
- Connections between LCA, LTA, and growth mixture modeling
Day 1: Introduction to latent class analysis (LCA)
- Conceptual introduction to LCA
- An example: latent classes of adolescent drinking behavior
- Parameters estimated in LCA
- Technical considerations: model identification, model selection
- Software options
Day 2: Adding features to “baseline” models
- Including a grouping variable
- Review of logistic regression
- Predicting latent class membership
- Predicting a distal outcome
- Conceptual introduction to latent profile analysis (LPA)
Day 3: Introduction to latent transition analysis (LTA)
- Conceptual introduction to LTA
- An example: latent classes of dating and sexual risk behavior
- Technical details
- Including a grouping variable
- Predicting transitions
- Connections between LCA, LTA, and growth mixture modeling
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.