Department of Psychology, University of Pittsburgh, Pittsburgh, PA.
Nicotine Tob Res. 2014 May;16 Suppl 2(Suppl 2):S76-87. doi: 10.1093/ntr/ntt195. Epub 2013 Dec 9.
Ecological momentary assessment (EMA) methods, which involve collection of real-time data in subjects' real-world environments, are particularly well suited to studying tobacco use. Analyzing EMA datasets can be challenging, as the datasets include a large and varied number of observations per subject and are relatively unstructured. This paper suggests that time is typically a key organizing principle in EMA data and that conceptualizing the data as a timeline of events, behaviors, and experiences can help define analytic approaches. EMA datasets lend themselves to answering a diverse array of research questions, and the research question must drive how data are arranged for analysis, and the kinds of statistical models that are applied. This is illustrated this with brief examples of diverse analyses applied to answer different questions from an EMA study of tobacco use and relapse.
生态瞬时评估（EMA）方法涉及在研究对象的真实环境中收集实时数据，特别适合研究烟草使用情况。分析 EMA 数据集具有一定的挑战性，因为每个研究对象的数据集都包含大量且多样的观测值，并且相对没有结构。本文认为，时间通常是 EMA 数据的一个关键组织原则，将数据概念化为事件、行为和经验的时间线可以帮助定义分析方法。EMA 数据集可用于回答各种研究问题，并且研究问题必须决定如何为分析安排数据，以及应用哪种类型的统计模型。本文通过简要介绍从烟草使用和复发的 EMA 研究中应用于回答不同问题的各种分析示例来说明这一点。
