Wang Hao, Shiffman Saul, Griffith Sandra D, Heitjan Daniel F
Johns Hopkins University.
University of Pittsburgh.
Ann Appl Stat. 2012;6(4):1689-1706. doi: 10.1214/12-AOAS557.
Studies of smoking behavior commonly use the method, or periodic retrospective recall, to gather data on daily cigarette consumption. TLFB is considered adequate for identifying periods of abstinence and lapse but not for measurement of daily cigarette consumption, thanks to substantial recall and digit preference biases. With the development of the hand-held electronic diary (ED), it has become possible to collect cigarette consumption data using , or the instantaneous recording of each cigarette as it is smoked. EMA data, because they do not rely on retrospective recall, are thought to more accurately measure cigarette consumption. In this article we present an analysis of consumption data collected simultaneously by both methods from 236 active smokers in the pre-quit phase of a smoking cessation study. We define a statistical model that describes the genesis of the TLFB records as a two-stage process of mis-remembering and rounding, including fixed and random effects at each stage. We use Bayesian methods to estimate the model, and we evaluate its adequacy by studying histograms of imputed values of the latent remembered cigarette count. Our analysis suggests that both mis-remembering and heaping contribute substantially to the distortion of self-reported cigarette counts. Higher nicotine dependence, white ethnicity and male sex are associated with greater remembered smoking given the EMA count. The model is potentially useful in other applications where it is desirable to understand the process by which subjects remember and report true observations.
吸烟行为研究通常采用时间线跟进法（TLFB）或定期回顾性回忆法来收集每日香烟消费量的数据。由于存在大量的回忆偏差和数字偏好偏差，TLFB被认为足以识别戒烟期和复吸期，但不适用于测量每日香烟消费量。随着手持电子日记（ED）的发展，使用事件记录法，即每吸一支烟时即时记录，来收集香烟消费数据已成为可能。由于生态瞬时评估（EMA）数据不依赖回顾性回忆，因此被认为能更准确地测量香烟消费量。在本文中，我们对来自一项戒烟研究的236名处于戒烟前阶段的现吸烟者通过这两种方法同时收集的消费数据进行了分析。我们定义了一个统计模型，该模型将TLFB记录的产生描述为一个包括记忆错误和舍入的两阶段过程，在每个阶段都有固定效应和随机效应。我们使用贝叶斯方法来估计该模型，并通过研究潜在记忆香烟数量的插补值直方图来评估其适用性。我们的分析表明，记忆错误和堆积都对自我报告的香烟数量的扭曲有很大影响。在考虑EMA计数的情况下，更高的尼古丁依赖、白人种族和男性性别与更多的记忆吸烟量相关。该模型在其他希望了解受试者记忆和报告真实观察结果过程的应用中可能会很有用。
