This course teaches you how to analyze linear mixed models using the MIXED procedure. A brief introduction to analyzing generalized linear mixed models using the GLIMMIX procedure is also included.
- 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 Can Benefit
- Statisticians, experienced data analysts, and researchers with sound statistical knowledge
- 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.