IC18: Longitudinal Data Analysis and Practical Workshop using R: Part II Advanced Topics

Monday, November 7, 2022

1:30 PM – 5:30 PM

Presenter(s)

Allan J. Kozlowski, PhD, B.Sc. (PT)

Consultant
Mary Free Bed Rehabilitation Hospital
Grand Rapids, Michigan, United States

Slides Slides and Audio
Keith Lohse, PhD, PStat

Associate Professor
Washington University School of Medicine
Saint Louis, Missouri, United States

Slides

Rehabilitation researchers and clinicians often deal with outcomes that evolve over time and are not suited to binary categorization of pre- post-assessments, as is common in other areas of medicine and healthcare. This course will build on our previously offered introduction to modeling longitudinal outcomes in a lecture and practical workshop format. Advanced topics include methods to assess data and model structure visually, statistically, and conceptually; and to fit more complex models and outcome types. While not a prerequisite, course participants will benefit from having a working knowledge of the introductory course content and of the R environment.

Learning Objectives:

Describe the structure of curvilinear and non-linear (e.g., negative exponential) models
Examine relationships of data to model fit by examining data patterns over time
Discuss the use of fixed and time-varying covariates in curvilinear models
Fit models for curvilinear and non-linear (e.g., negative exponential) continuous outcomes in the R statistical environment