This paper presents an overview of analytic methods for estimating growth curves or developmental trajectories from longitudinal data. Traditional models for studying change are contrasted with a relatively new method, hierarchical linear models. Growth curve analyses of data from an early intervention project demonstrate the strengths and weaknesses of the various analytic methods. Using this example, evidence is presented indicating how hierarchical linear models can overcome some of the methodological limitations of other analytic techniques currently used to evaluate change.
Using growth curve analysis to evaluate child change in longitudinal investigations
Burchinal, MR., Bailey, D., & Snyder, P. (1994). Using growth curve analysis to evaluate child change in longitudinal investigations. Journal of Early Intervention, 18(4), 403-423. https://doi.org/10.1177/105381519401800409
Abstract
Publications Info
To contact an RTI author, request a report, or for additional information about publications by our experts, send us your request.
Meet the Experts
View All ExpertsRecent Publications
Article
Protection of forest ecosystems in the eastern United States from elevated atmospheric deposition of sulfur and nitrogen
Article
The use of patient experience feedback in rehabilitation quality improvement and codesign activities
Article
SPTSSA variants alter sphingolipid synthesis and cause a complex hereditary spastic paraplegia
OCCASIONAL PAPER