Group-Based Trajectory Modeling in Clinical Research

被引:1844
|
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
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
相关论文
共 50 条
  • [1] Recent Advances in Group-Based Trajectory Modeling for Clinical Research
    Nagin, Daniel S.
    Jones, Bobby L.
    Elmer, Jonathan
    ANNUAL REVIEW OF CLINICAL PSYCHOLOGY, 2024, 20 : 285 - 305
  • [2] Group-based Trajectory Modeling and Criminal Career Research
    Nagin, Daniel S.
    JOURNAL OF RESEARCH IN CRIME AND DELINQUENCY, 2016, 53 (03): : 356 - 371
  • [3] Group-Based Trajectory Modeling: An Overview
    Nagin, Daniel S.
    ANNALS OF NUTRITION AND METABOLISM, 2014, 65 (2-3) : 205 - 210
  • [4] Group-based multi-trajectory modeling
    Nagin, Daniel S.
    Jones, Bobby L.
    Passos, Valeria Lima
    Tremblay, Richard E.
    STATISTICAL METHODS IN MEDICAL RESEARCH, 2018, 27 (07) : 2015 - 2023
  • [5] Does group-based trajectory modeling estimate spurious trajectories?
    Miceline Mésidor
    Marie-Claude Rousseau
    Jennifer O’Loughlin
    Marie-Pierre Sylvestre
    BMC Medical Research Methodology, 22
  • [6] Group-Based Trajectory Modeling of Marital Quality: A Critical Review
    Proulx, Christine M.
    Ermer, Ashley E.
    Kanter, Jeremy B.
    JOURNAL OF FAMILY THEORY & REVIEW, 2017, 9 (03) : 307 - 327
  • [7] Group-Based Trajectory Modeling (Nearly) Two Decades Later
    Daniel S. Nagin
    Candice L. Odgers
    Journal of Quantitative Criminology, 2010, 26 : 445 - 453
  • [8] Group-Based Trajectory Modeling (Nearly) Two Decades Later
    Nagin, Daniel S.
    Odgers, Candice L.
    JOURNAL OF QUANTITATIVE CRIMINOLOGY, 2010, 26 (04) : 445 - 453
  • [9] Does group-based trajectory modeling estimate spurious trajectories?
    Mesidor, Miceline
    Rousseau, Marie-Claude
    O'Loughlin, Jennifer
    Sylvestre, Marie-Pierre
    BMC MEDICAL RESEARCH METHODOLOGY, 2022, 22 (01)
  • [10] Group-Based Trajectory Modeling of Suppression Ratio After Cardiac Arrest
    Jonathan Elmer
    John J. Gianakas
    Jon C. Rittenberger
    Maria E. Baldwin
    John Faro
    Cheryl Plummer
    Lori A. Shutter
    Christina L. Wassel
    Clifton W. Callaway
    Anthony Fabio
    Neurocritical Care, 2016, 25 : 415 - 423