Group-Based Trajectory Modeling in Clinical Research

被引:1857
作者
Nagin, Daniel S. [1 ]
Odgers, Candice L. [2 ]
机构
[1] Carnegie Mellon Univ, Heinz Sch Publ Policy, Pittsburgh, PA 15213 USA
[2] Univ Calif Irvine, Sch Social Ecol, Irvine, CA 92697 USA
来源
ANNUAL REVIEW OF CLINICAL PSYCHOLOGY, VOL 6 | 2010年 / 6卷
关键词
growth mixture modeling; longitudinal data; dual trajectory models; causal inference; ANALYZING DEVELOPMENTAL TRAJECTORIES; GROWTH MIXTURE-MODELS; CAUSAL INFERENCES; PROPENSITY SCORE; DISTRIBUTIONAL ASSUMPTIONS; DEPRESSIVE SYMPTOMS; GRADE RETENTION; SUBSTANCE-ABUSE; CHILDHOOD; HETEROGENEITY;
D O I
10.1146/annurev.clinpsy.121208.131413
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
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.
引用
收藏
页码:109 / 138
页数:30
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