Multilevel Modeling of Hierarchical and Longitudinal Data Using SAS®
BHLNM : BHLM42
This course teaches how to identify complex and dynamic patterns within multilevel data to inform a variety of decision-making needs. The course provides a conceptual understanding of multilevel linear models (MLM) and multilevel generalized linear models (MGLM) and their appropriate use in a variety of settings.
The self-study e-learning includes:
The self-study e-learning includes:
- Annotatable course notes in PDF format.
- Virtual lab time to practice.
Learn How To
- Use basic multilevel models.
- Use three-level and cross-classified models.
- Use generalized multilevel models for discrete dependent variables.
Who Should Attend
Researchers in psychology, education, social science, medicine, and business, or others analyzing data with multilevel nesting structure
Prerequisites
Before attending this course, you should:
- Preferably, be familiar with the basic structure and concepts of SAS (for example, the DATA step and procedures).
- Be familiar with concepts of linear models such as regression and ANOVA and with generalized linear models such as logistic regression.
- Be familiar with linear mixed models to enhance understanding, although this is not necessary to benefit from the course.
SAS Products Covered
SAS/STAT
Course Outline
Introduction to Multilevel Models
- Nested data structures.
- Ignoring dependence.
- Methods for modeling dependent data structures.
- The random-effects ANOVA model.
- Random-effects regression.
- Centering predictors in multilevel models.
- Model building.
- A comment on notation (self-study).
- Intercepts as outcomes.
- Slopes as outcomes.
- Model assumptions.
- Model assessment and diagnostics.
- Maximum likelihood estimation.
- The conceptualization of a growth curve.
- The multilevel growth model.
- Time-invariant predictors of growth (self-study).
- Multiple groups models.
- Three-level models.
- Three-level models with random slopes.
- Cross-classified models.
- Discrete dependent variables.
- Generalized linear models.
- Multilevel generalized linear models.
- Additional considerations.
- Complexities of longitudinal data structures.
- The unconditional growth model for discrete dependent variables.
- Conditional growth models for discrete dependent variables.
Live Class Schedule
Duration: 14 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
This course isn't publicly scheduled, but private training and mentoring may be available. Contact us to explore options.
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.