Translated by WANG Weiwei 1 , ZHANG Ge 2 , ZHOU Qingxin 3 , LV Xiaozhen 4 , MENG Ruogu 5 , YANG Zhirong 6 , SUN Feng 3
  • 1. The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, P.R.China;
  • 2. Zhangfan Information Technology (Shanghai) Co., Ltd, Shanghai, 200090, P.R.China;
  • 3. Department of Epidemiology and Biostatistics, School of Public Health, Center of Evidence-based Medicine and Clinical Research, Peking University, Beijing, 100191, P.R.China;
  • 4. Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, 100191, P.R.China;
  • 5. National Institute of Health Data Science, Center for Data Science in Health and Medicine, Peking University, Beijing, 100191, P.R.China;
  • 6. Primary Care Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB1 8RN, UK;
SUN Feng, Email: sunfeng@bjmu.edu.cn
潜类别; LCGA; LGMM; 混合模型; 结构方程模型
10.7507/1672-2531.201910053
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混合模型框架下的模型，如潜变量增长混合模型（latent growth mixture modeling，LGMM）或潜类别增长分析（latent class growth analysis，LCGA），因估算过程中涉及多个决策过程，导致潜变量轨迹分析结果的报告呈现多样性。为解决这一问题，指南制订小组按照系统化的制订流程，通过 4 轮德尔菲法调查，遵循专家小组意见，提出了各领域报告潜变量轨迹分析结果时需采用统一的标准，最终确定了报告轨迹研究结果必要的关键条目，发布了潜变量轨迹研究报告规范（guidelines for reporting on latent trajectory studies，GRoLTS），并利用 GRoLTS 评价了 38 篇使用 LGMM 或 LCGA 研究创伤后应激轨迹的论文的报告情况。