Department of Public Health Sciences, The University of Chicago, Chicago, IL, USA.
Institute for Health Research and Policy, University of Illinois at Chicago, Chicago, IL, USA.
Stat Med. 2018 Jun 15;37(13):2108-2119. doi: 10.1002/sim.7627. Epub 2018 Feb 26.
Ecological momentary assessment studies usually produce intensively measured longitudinal data with large numbers of observations per unit, and research interest is often centered around understanding the changes in variation of people's thoughts, emotions and behaviors. Hedeker et al developed a 2-level mixed effects location scale model that allows observed covariates as well as unobserved variables to influence both the mean and the within-subjects variance, for a 2-level data structure where observations are nested within subjects. In some ecological momentary assessment studies, subjects are measured at multiple waves, and within each wave, subjects are measured over time. Li and Hedeker extended the original 2-level model to a 3-level data structure where observations are nested within days and days are then nested within subjects, by including a random location and scale intercept at the intermediate wave level. However, the 3-level random intercept model assumes constant response change rate for both the mean and variance. To account for changes in variance across waves, as well as clustering attributable to waves, we propose a more comprehensive location scale model that allows subject heterogeneity at baseline as well as across different waves, for a 3-level data structure where observations are nested within waves and waves are then further nested within subjects. The model parameters are estimated using Markov chain Monte Carlo methods. We provide details on the Bayesian estimation approach and demonstrate how the Stan statistical software can be used to sample from the desired distributions and achieve consistent estimates. The proposed model is validated via a series of simulation studies. Data from an adolescent smoking study are analyzed to demonstrate this approach. The analyses clearly favor the proposed model and show significant subject heterogeneity at baseline as well as change over time, for both mood mean and variance. The proposed 3-level location scale model can be widely applied to areas of research where the interest lies in the consistency in addition to the mean level of the responses.
生态瞬时评估研究通常会产生密集测量的纵向数据,每个单位有大量的观测值,研究兴趣通常集中在理解人们的思想、情感和行为变化的规律上。Hedeker 等人开发了一种 2 水平混合效应位置尺度模型,该模型允许观察到的协变量以及未观察到的变量同时影响均值和个体内方差,适用于观测值嵌套在个体内的 2 水平数据结构。在一些生态瞬时评估研究中,个体在多个波次中进行测量,并且在每个波次中,个体随时间进行测量。Li 和 Hedeker 通过在中间波次水平上包含随机位置和尺度截距,将原始的 2 水平模型扩展到 3 水平数据结构,其中观测值嵌套在天内,然后天嵌套在个体内。然而,3 水平随机截距模型假设均值和方差的响应变化率保持不变。为了说明跨波次方差的变化以及归因于波次的聚类,我们提出了一种更全面的位置尺度模型,该模型允许在基线以及不同波次中存在个体异质性,适用于观测值嵌套在波次内,然后波次进一步嵌套在个体内的 3 水平数据结构。模型参数通过马尔可夫链蒙特卡罗方法进行估计。我们提供了贝叶斯估计方法的详细信息,并演示了如何使用 Stan 统计软件从所需分布中抽样并获得一致的估计。通过一系列模拟研究验证了所提出的模型。对青少年吸烟研究的数据进行了分析,以展示该方法。分析结果明显支持所提出的模型,并显示出在基线以及随时间变化时,情绪均值和方差都存在显著的个体异质性。所提出的 3 水平位置尺度模型可以广泛应用于研究领域,这些领域的研究兴趣不仅在于响应的均值水平,还在于其一致性。