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Analysis of nonlinear patterns of change with random coefficient models
Robert Cudeck1, Jeffrey R Harring
1Psychology Department, Ohio State University, Columbus, Ohio 43210, USA. cudeck.1@osu.edu
Annual Review of Psychology
|September 7, 2006
Summary
This study reviews nonlinear random coefficient models for analyzing longitudinal psychology data. These models capture rapid developmental changes and individual differences in response patterns over time.
Area of Science:
- Psychology
- Statistics
- Longitudinal Data Analysis
Background:
- Nonlinear change patterns are common in psychological longitudinal studies.
- Developmental changes often occur at varying rates across different periods.
- Significant individual differences (heterogeneity) in response trajectories are frequently observed.
Purpose of the Study:
- To review and illustrate the application of nonlinear random coefficient models.
- To provide a statistically sound method for analyzing subject-specific nonlinear development.
- To describe methods for accommodating heterogeneity in longitudinal data.
Main Methods:
- Extension of the random coefficient model to nonlinear trajectories.
- Statistical modeling of repeated measures data.
- Illustrative examples using concrete data scenarios.
Main Results:
- Nonlinear random coefficient models effectively describe nonlinear developmental trajectories.
- These models can account for substantial individual differences in response patterns.
- The approach offers a statistically satisfying analysis of subject-specific development.
Conclusions:
- Nonlinear random coefficient models are valuable tools for psychological longitudinal research.
- These models provide a robust framework for understanding complex developmental changes.
- The reviewed methods offer insights into individual heterogeneity in growth patterns.
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