Trajectory Modelling Techniques Useful to Epidemiological Research: A Comparative Narrative Review of Approaches.
Trajectory Modelling Techniques Useful to Epidemiological Research: A Comparative Narrative Review of Approaches.
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DOI：
10.2147/clep.s265287
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发表时间：
2020
影响因子：
3.9
通讯作者：
Lacasse A
中科院分区：
文献类型：
--
作者：
Nguena Nguefack HL;Pagé MG;Katz J;Choinière M;Vanasse A;Dorais M;Samb OM;Lacasse A
发展轨迹建模技术以确定特定人群中的亚群，并越来越多地用于更好地了解健康结果模式随时间变化的个体内部和个体间变异性。这篇叙述性综述的目的是探索对流行病学研究有用的各种轨迹建模方法，并概述其应用和差异。报告轨迹建模结果的指导也包括在内。回顾的轨迹建模技术包括潜在类建模方法，即生长混合模型（GMM）、基于群体的轨迹建模（GBTM）、潜在类分析（LCA）和潜在转移分析（LTA）。与其他以个人为中心的统计方法类似，如聚类分析（CA）和序列分析（SA）。根据研究问题和数据类型，可以使用许多方法对纵向研究中测量的健康结果进行轨迹建模。然而，在现有的科学文献中，用于指定潜在类建模方法的各种术语（GMM， GBTM， LTA， LCA）的使用不一致，并且经常互换。当涉及到选择最适合他们的研究问题的最合适的技术时，术语和报告指南的改进一致性有可能提高科学家的效率。
Trajectory modelling techniques have been developed to determine subgroups within a given population and are increasingly used to better understand intra- and inter-individual variability in health outcome patterns over time. The objectives of this narrative review are to explore various trajectory modelling approaches useful to epidemiological research and give an overview of their applications and differences. Guidance for reporting on the results of trajectory modelling is also covered. Trajectory modelling techniques reviewed include latent class modelling approaches, ie, growth mixture modelling (GMM), group-based trajectory modelling (GBTM), latent class analysis (LCA), and latent transition analysis (LTA). A parallel is drawn to other individual-centered statistical approaches such as cluster analysis (CA) and sequence analysis (SA). Depending on the research question and type of data, a number of approaches can be used for trajectory modelling of health outcomes measured in longitudinal studies. However, the various terms to designate latent class modelling approaches (GMM, GBTM, LTA, LCA) are used inconsistently and often interchangeably in the available scientific literature. Improved consistency in the terminology and reporting guidelines have the potential to increase researchers’ efficiency when it comes to choosing the most appropriate technique that best suits their research questions.