Multilevel Modeling of Hierarchical and Longitudinal Data Using SAS®

This course teaches students 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.

Voraussetzungen
Before attending this course, participants should have basic understanding of SAS procedures for producing summary statistics and graphs, such as the MEANS and SGPLOT procedures and basic knowledge and experience in linear regression models (PROC REG).

Zielgruppe
Researchers in psychology, education, social science, medicine, and business.

Module
SAS/STAT, SAS/GRAPH Software

Kursinhalte

• Introduction to Multilevel Models
  • nested data structures
  • ignoring dependence
  • methods for modeling dependent data structures
  • the random-effects ANOVA model
• Basic Multilevel Models
  • random-effects regression
  • centering predictors in multilevel models
  • model building
  • a comment on notation (self-study)
  • intercepts as outcomes
• Slopes as Outcomes and Model Evaluation
  • slopes as outcomes
  • model assumptions
  • model assessment and diagnostics
  • maximum likelihood estimation
• The Analysis of Repeated Measures
  • the conceptualization of a growth curve
  • the multilevel growth model
  • time-invariant predictors of growth (self-study)
  • multiple groups models
• Three-Level and Cross-Classified Models
  • three-level models
  • three-level models with random slopes
  • cross-classified models
• Multilevel Models for Discrete Dependent Variables
  • discrete dependent variables
  • generalized linear models
  • multilevel generalized linear models
  • additional considerations
• Generalized Multilevel Linear Models for Longitudinal Data (Self-Study)
  • complexities of longitudinal data structures
  • the unconditional growth model for discrete dependent variables
  • conditional growth models for discrete dependent variables

Referent
This course will be held by Dr. Catherine Truxillo or Chris Daman , Statistical Services Specialists, Education Division, SAS.

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