title: Analysis of nonlinear patterns of change with random coefficient models.
abstract: Nonlinear patterns of change arise frequently in the analysis of repeated measures from longitudinal studies in psychology. The main feature of nonlinear development is that change is more rapid in some periods than in others. There generally also are strong individual differences, so although there is a general similarity of patterns for different persons over time, individuals exhibit substantial heterogeneity in their particular response. To describe data of this kind, researchers have extended the random coefficient model to accommodate nonlinear trajectories of change. It can often produce a statistically satisfying account of subject-specific development. In this review we describe and illustrate the main ideas of the nonlinear random coefficient model with concrete examples.
authors.affiliation: Psychology Department, Ohio State University, Columbus, Ohio 43210, USA. cudeck.1@osu.edu
authors.forename: Robert
authors.initials: R
authors.lastname: Cudeck
authors.forename: Jeffrey R
authors.initials: JR
authors.lastname: Harring
mesh_terms: D000704:Analysis of Variance; D001525:Behavioral Sciences / Q000706:statistics & numerical data*; D002648:Child; D002675:Child, Preschool; D003196:Computer Graphics / Q000706:statistics & numerical data; D006801:Humans; D007206:Individuality; D007804:Language Development; D008137:Longitudinal Studies; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D009949:Orientation; D010364:Pattern Recognition, Visual; D011214:Practice, Psychological; D011597:Psychomotor Performance; D011930:Reaction Time; D011932:Reading; D012858:Size Perception; D013068:Speech Production Measurement / Q000706:statistics & numerical data; D014792:Visual Acuity