A Cautionary Note on Modeling Growth Trends in Longitudinal Data

Random coefficient and latent growth curve modeling are currently the dominant approaches to the analysis of longitudinal data in psychology. The application of these models to longitudinal data assumes that the data-generating mechanism behind the psychological process under investigation contains...

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Bibliographic Details
Published inPsychological methods Vol. 16; no. 3; pp. 249 - 264
Main Authors Kuljanin, Goran, Braun, Michael T, DeShon, Richard P
Format Journal Article
LanguageEnglish
Published United States American Psychological Association 01.09.2011
Subjects
Behavioral Research - methods
Humans
Longitudinal Studies
Longitudinal Studies - methods
Models, Statistical
Monte Carlo Method
Psychological Studies
Psychology - methods
Regression (Statistics)
Regression Analysis
Stochastic Processes
Trend Analysis
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Summary:Random coefficient and latent growth curve modeling are currently the dominant approaches to the analysis of longitudinal data in psychology. The application of these models to longitudinal data assumes that the data-generating mechanism behind the psychological process under investigation contains only a deterministic trend. However, if a process, at least partially, contains a stochastic trend, then random coefficient regression results are likely to be spurious. This problem is demonstrated via a data example, previous research on simple regression models, and Monte Carlo simulations. A data analytic strategy is proposed to help researchers avoid making inaccurate inferences when observed trends may be due to stochastic processes. (Contains 4 figures, 2 footnotes and 4 tables.)
ISSN:1082-989X
1939-1463
DOI:10.1037/a0023348