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:
- Annotatable course notes in PDF format.
- Virtual lab time to practice.
Lernen Sie, wie Sie / Learn how to
- Use basic multilevel models.
- Use three-level and cross-classified models.
- Use generalized multilevel models for discrete dependent variables.
Zielgruppe / Who should attend
Researchers in psychology, education, social science, medicine, and business, or others analyzing data with multilevel nesting structure
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.
It is recommended that you complete SAS® Programmierung 1: Grundlagen and Statistics 2: ANOVA and Regression or have equivalent knowledge before taking this course.
In diesem Kurs wird mit folgenden Software Modulen gearbeitet / This course addresses SAS/STAT Software