范畴变量
损耗
弹道
心理学
主题(文档)
计算机科学
数据科学
计量经济学
认知心理学
机器学习
医学
数学
图书馆学
物理
天文
牙科
作者
Daniel S. Nagin,Bobby L. Jones,Jonathan Elmer
标识
DOI:10.1146/annurev-clinpsy-081122-012416
摘要
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.
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