Journal
REHABILITATION PSYCHOLOGY
Volume 53, Issue 3, Pages 370-386Publisher
EDUCATIONAL PUBLISHING FOUNDATION-AMERICAN PSYCHOLOGICAL ASSOC
DOI: 10.1037/a0012765
Keywords
multilevel model; growth model; trajectory analysis; hierarchical linear model; rehabilitation
Categories
Ask authors/readers for more resources
Objective: The use and quality of longitudinal research designs has increased over the past 2 decades, and new approaches for analyzing longitudinal data, including multilevel modeling (MLM) and latent growth modeling (LGM), have been developed. The purpose of this article is to demonstrate the use of MLM and its advantages in analyzing longitudinal data. Research Method: Data from a sample of individuals with intra-articular fractures of the lower extremity from the University of Alabama at Birmingham's Injury Control Research Center are analyzed using both SAS PROC MIXED and SPSS MIXED. Results: The authors begin their presentation with a discussion of data preparation for MLM analyses. The authors then provide example analyses of different growth models, including a simple linear growth model and a model with a time-invariant covariate, with interpretation for all the parameters in the models. Implications: More complicated growth models with different between- and within-individual covariance structures and nonlinear models are discussed. Finally, information related to MLM analysis, such as online resources, is provided at the end of the article.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available