Group-based trajectory modeling (GBTM) identifies groups of individuals following similar trajectories of one or more repeated measures. The categorical nature of GBTM is particularly well suited to clinical psychology and medicine, where patients are often classified into discrete diagnostic categories. This review highlights recent advances in GBTM and key capabilities that remain underappreciated in clinical research. These include accounting for nonrandom subject attrition, joint trajectory and multitrajectory modeling, the addition of the beta distribution to modeling options, associating trajectories with future outcomes, and estimating the probability of future outcomes. Also discussed is an approach to selecting the number of trajectory groups.Expected final online publication date for the Annual Review of Clinical Psychology, Volume 20 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

中文翻译：

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临床研究基于组的轨迹建模的最新进展

基于群体的轨迹建模 (GBTM) 可识别遵循一项或多项重复测量的相似轨迹的个体群体。 GBTM 的分类性质特别适合临床心理学和医学，患者通常被分为离散的诊断类别。本综述重点介绍了 GBTM 的最新进展以及临床研究中仍未得到充分重视的关键功能。这些包括考虑非随机受试者损耗、联合轨迹和多轨迹建模、在建模选项中添加贝塔分布、将轨迹与未来结果相关联以及估计未来结果的概率。还讨论了选择轨迹组数量的方法。《临床心理学年度评论》第 20 卷的预计最终在线发布日期为 2024 年 5 月。请参阅 http://www.annualreviews.org/page/journal/pubdates修订后的估计。