Analysis of Nonlinear Patterns of Change with Random Coefficient
Models
R. Cudeck, and J. Harring. Social Science Research Network Working Paper Series, (2007)
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.
%0 Journal Article
%1 Cudeck2007
%A Cudeck, Robert
%A Harring, Jeffrey
%D 2007
%I SSRN
%J Social Science Research Network Working Paper Series
%K chronobiology, statistics
%P --
%T Analysis of Nonlinear Patterns of Change with Random Coefficient
Models
%U http://ssrn.com/abstract=1077435
%X 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.
@article{Cudeck2007,
__markedentry = {[freesurfer:6]},
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.},
added-at = {2012-02-24T14:11:06.000+0100},
author = {Cudeck, Robert and Harring, Jeffrey},
biburl = {https://www.bibsonomy.org/bibtex/2414f111debef5382df68e25c2c81c206/jakspa},
interhash = {89783005b874c6aa162c4bdb08b3a00b},
intrahash = {414f111debef5382df68e25c2c81c206},
journal = {Social Science Research Network Working Paper Series},
keywords = {chronobiology, statistics},
owner = {freesurfer},
pages = {--},
publisher = {SSRN},
refid = {citeulike:10382004},
timestamp = {2012-02-24T14:11:07.000+0100},
title = {Analysis of Nonlinear Patterns of Change with Random Coefficient
Models},
url = {http://ssrn.com/abstract=1077435},
year = 2007
}