Invited Commentary: The Tao of Clinical Cohort Analysis-When the Transitions That Can Be Spoken of Are Not the True Transitions.
Invited Commentary: The Tao of Clinical Cohort Analysis-When the Transitions That Can Be Spoken of Are Not the True Transitions.
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特邀评论：临床队列分析之道——当可以说的转变不是真正的转变时。
DOI：
10.1093/aje/kww236
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发表时间：
2017
影响因子：
5
通讯作者：
Mooney,StephenJ
中科院分区：
文献类型：
--
作者：
Mooney,StephenJ
使用临床部署的调查确定的风险相关行为模式可能对公共卫生监测具有价值。然而，由于此类调查仅在受试者选择访问诊所时评估受试者，因此临床数据受到观察模式的变化的影响，而这在研究团队定期与受试者接触的传统纵向数据集中不存在。在本期杂志中，威尔金森等人（美国流行病学杂志。2017;185（8）：627-635）描述了他们如何将潜在转换分析技术应用于临床访视期间收集的监测数据。在这篇评论中，我讨论了由于受试者特异性观察模式而可能在临床数据纵向分析中出现的选择偏倚，特别关注由于将连续临床访视分类为波而可能出现的问题。我认为，定量偏倚分析和逆概率加权可能是有用的技术，以评估和控制偏差在未来的潜在过渡分析的临床数据。
Patterns in risk-related behaviors identified using clinically deployed surveys may hold value for public health surveillance. However, because such surveys assess subjects only when subjects choose to visit clinics, clinical data are subject to variability in observation patterns that is not present in conventional longitudinal data sets in which research teams contact subjects at regular intervals. In this issue of theJournal, Wilkinson et al. (Am J Epidemiol. 2017;185(8):627–635) describe how they applied a latent transition analysis technique to surveillance data collected during clinic visits. In this commentary I discusses the selection bias that may arise in longitudinal analysis of clinical data due to subject-specific observation patterns, with particular focus on issues that may arise due to classifying successive clinical visits as waves. I suggest that quantitative bias analysis and inverse probability weighting may be useful techniques with which to assess and control bias in future latent transition analyses of clinical data.