Analyzing developmental trajectories of distinct but related behaviors: A group-based method.
Abstract
This article presents a group-based method to jointly estimate developmental trajectories of 2 distinct but theoretically related measurement series. The method will aid the analysis of comorbidity and heterotypic continuity. Three key outputs of the model are (a) for both measurement series, the form of the trajectory of distinctive subpopulations; (b) the probability of membership in each such trajectory group; and (c) the joint probability of membership in trajectory groups across behaviors. This final output offers 2 novel features. First, the joint probabilities can characterize the linkage in the developmental course of distinct but related behaviors. Second, the joint probabilities can measure differences within the population in the magnitude of this linkage. Two examples are presented to illustrate the application of the method.
Cites (6)
- Bayes factorsKass, Robert E., Raftery, Adrian E. · 1995 · Journal of the American Statistical Association
- Lifetime and 12-Month Prevalence of DSM-III-R Psychiatric Disorders in the United States: Results From the National Comorbidity SurveyKessler, Ronald C. · 1994 · Archives of General Psychiatry
- A General Theory of CrimeGottfredson, Michael R., Hirschi, Travis · 1990
- Adolescence-limited and life-course-persistent antisocial behavior: a developmental taxonomyMoffitt, Terrie E. · 1993 · Psychological Review
- Analyzing developmental trajectories: A semiparametric, group-based approach.Nagin, Daniel S. · 1999 · Psychological Methods
- A developmental perspective on antisocial behaviorPatterson, G. R., DeBaryshe, Barbara D., Ramsey, Elizabeth · 1989 · American Psychologist
Cited by (52)
- Group-Based Trajectory Modeling in Clinical ResearchNagin, Daniel S., Odgers, Candice L. · 2010 · Annual Review of Clinical Psychology
- Prior Juvenile Diagnoses in Adults With Mental Disorder: Developmental Follow-Back of a Prospective-Longitudinal CohortKim-Cohen, Julia, Caspi, Avshalom, Moffitt, Terrie E., Harrington, HonaLee, Milne, Barry J., Poulton, Richie · 2003 · Archives of General Psychiatry
- Latent Variable Analysis: Growth Mixture Modeling and Related Techniques for Longitudinal DataMuthén, Bengt · 2004 · The SAGE Handbook of Quantitative Methodology for the Social Sciences
- Developmental trajectories of childhood disruptive behaviors and adolescent delinquency: A six-site, cross-national study.Broidy, Lisa M., Nagin, Daniel S., Tremblay, Richard E., Bates, John E., Brame, Bobby, Dodge, Kenneth A., Fergusson, David, Horwood, John L., Loeber, Rolf, Laird, Robert et al. · 2003 · Developmental Psychology
- Methods and measures: growth mixture modeling: a method for identifying differences in longitudinal change among unobserved groupsRam, Nilam, Grimm, Kevin J. · 2009 · International Journal of Behavioral Development
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Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Analyzing developmental trajectories of distinct but related behaviors: A group-based method. https://app.cochat.ai/papers/10.1037//1082-989x.6.1.18
- The paper
- Nagin, D. S., & Tremblay, R. E. (2001). Analyzing developmental trajectories of distinct but related behaviors: A group-based method. Psychological Methods. https://doi.org/10.1037//1082-989x.6.1.18
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