Instructional Course

Measurement

Cross-Cutting

IC6: Longitudinal Data Analysis and Practical Workshop Using R: Part I Introductory Topics (823276)

Presenter(s)

• 

  Allan J. Kozlowski, PhD

  Director of Outcomes Research
  Mary Free Bed Rehabilitation Hospital
  Grand Rapids, Michigan

  Presentation Slides Presentation + Audio
• 

  Keith Lohse, PhD

  Assistant Professor, Health and Kinesiology
  University of Utah
  Salt Lake City, Utah

This combination lecture and hands-on workshop will introduce clinicians and researchers to longitudinal model building using linear mixed effects regression (LMER) in the R statistical environment. Rehabilitation outcomes are better suited to multi-level longitudinal modeling than to pre-post regression or repeated measures analysis of variance (RM-ANOVA). LMER has real advantages over RM-ANOVA in terms of flexibility and statistical power. Following the course, learners will be able to appraise existing data for suitability to LMER, discuss the relevance of such models with statistical consultants, and plan for data collection in future projects which are suited to modeling outcomes longitudinally.

Learning Objectives:

• Identify circumstances in which longitudinal mixed-effects regression (LMER) models are appropriate
• Discuss measurement issues in rehabilitation related to LMER
• Describe a process for examining longitudinal data and determining a best-fit linear trajectory
• Describe a process for evaluating covariate associations with trajectory parameters
• Build longitudinal linear two-level models of time nested within persons using the R statistical environment