期刊
ANNUAL REVIEW OF CLINICAL PSYCHOLOGY, VOL 6
卷 6, 期 -, 页码 109-138出版社
ANNUAL REVIEWS
DOI: 10.1146/annurev.clinpsy.121208.131413
关键词
growth mixture modeling; longitudinal data; dual trajectory models; causal inference
资金
- NIMH NIH HHS [R01 MH65611-01A2] Funding Source: Medline
- NATIONAL INSTITUTE OF MENTAL HEALTH [R01MH065611] Funding Source: NIH RePORTER
Group-based trajectory models are increasingly being applied in clinical research to map the developmental course of symptoms and assess heterogeneity in response to clinical interventions. In this review, we provide a nontechnical overview of group-based trajectory and growth mixture modeling alongside a sampling of how these models have been applied in clinical research. We discuss the challenges associated with the application of both types of group-based models and propose a set of preliminary guidelines for applied researchers to follow when reporting model results. Future directions in group-based modeling applications are discussed, including the use of trajectory models to facilitate causal inference when random assignment to treatment condition is not possible.
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