Mixed Models Analyses Using SAS®
AGLM : AGLM42
Learn How To
- analyze data (including binary data) with random effects
- fit random coefficient models and hierarchical linear models
- analyze repeated measures data
- obtain and interpret the best linear unbiased predictions
- perform residual and influence diagnostic analysis
- address convergence issues.
Who Should Attend
Statisticians, experienced data analysts, and researchers with sound statistical knowledge
Prerequisites
Before attending this course, you should
- know how to create and manage SAS data sets
- have experience performing analysis of variance using the GLM procedure of SAS/STAT software
- have completed and mastered the Statistics 2: ANOVA and Regression course or completed a graduate-level course on general linear models
- have an understanding of generalized linear models and their analysis.
SAS Products Covered
SAS/STAT
Course Outline
Introduction to Mixed Models
- identifying fixed and random effects
- describing linear mixed model equations and assumptions
- fitting a linear mixed model for a randomized complete block design using the MIXED procedure
- writing CONTRAST and ESTIMATE statements to perform custom hypothesis tests
- fitting a linear mixed model for two-way mixed models
- fitting a linear mixed model for nested mixed models
- fitting a linear mixed model for split-plot designs
- fitting a linear mixed model for crossover designs
- fitting analysis of covariance models with random effects
- performing random coefficient regression analysis
- conducting hierarchical linear modeling
- explaining BLUPs and EBLUPs
- producing parameter estimates associated with the fixed effects and random effects
- explaining the difference between LSMEANS and EBLUPs
- computing LSMEANS and EBLUPs using the MIXED procedure
- discussing issues on repeated measures analysis, including modeling covariance structure
- analyzing repeated measures data using the four-step process with the MIXED procedure
- performing residual and influence diagnostics for linear mixed models
- troubleshooting convergence problems
- discussing issues associated with unbalanced data, data with empty cells, estimation and inference of variance parameters, and different denominator degrees of freedom estimation methods
- discussing the situations where generalized linear mixed models and nonlinear mixed models analysis are needed
- performing the analysis for generalized linear mixed models using the GLIMMIX procedure
Live Class Schedule
Duration: 21 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.
Live Class Schedule
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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.
Coaching Services
Take your training to the next level with personalized coaching. While private training offers structured coursework, coaching 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.