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一种应用于生态瞬时评估(EMA)数据的双变量混合效应位置尺度模型。

A Bivariate Mixed-Effects Location-Scale Model with application to Ecological Momentary Assessment (EMA) data.

作者信息

Pugach Oksana, Hedeker Donald, Mermelstein Robin

机构信息

Institute for Health Research and Policy, University of Illinois at Chicago.

Institute for Health Research and Policy, University of Illinois at Chicago ; Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago.

出版信息

Health Serv Outcomes Res Methodol. 2014 Dec;14(4):194-212. doi: 10.1007/s10742-014-0126-9.

Abstract

A bivariate mixed-effects location-scale model is proposed for estimation of means, variances, and covariances of two continuous outcomes measured concurrently in time and repeatedly over subjects. Modeling the two outcomes jointly allows examination of BS and WS association between the outcomes and whether the associations are related to covariates. The variance-covariance matrices of the BS and WS effects are modeled in terms of covariates, explaining BS and WS heterogeneity. The proposed model relaxes assumptions on the homogeneity of the within-subject (WS) and between-subject (BS) variances. Furthermore, the WS variance models are extended by including random scale effects. Data from a natural history study on adolescent smoking are used for illustration. 461 students, from 9 and 10 grades, reported on their mood at random prompts during seven consecutive days. This resulted in 14,105 prompts with an average of 30 responses per student. The two outcomes considered were a subject's positive affect and a measure of how tired and bored they were feeling. Results showed that the WS association of the outcomes was negative and significantly associated with several covariates. The BS and WS variances were heterogeneous for both outcomes, and the variance of the random scale effects were significantly different from zero.

摘要

提出了一种双变量混合效应位置尺度模型,用于估计在时间上同时测量且在受试者中重复测量的两个连续结局的均值、方差和协方差。对这两个结局进行联合建模,可以检验结局之间的组内(WS)和组间(BS)关联,以及这些关联是否与协变量相关。根据协变量对BS和WS效应的方差协方差矩阵进行建模,解释了BS和WS的异质性。所提出的模型放宽了关于受试者内(WS)和受试者间(BS)方差同质性的假设。此外,通过纳入随机尺度效应扩展了WS方差模型。以一项关于青少年吸烟的自然史研究数据为例进行说明。461名九、十年级学生连续七天在随机提示下报告自己的情绪。这产生了14105个提示,平均每名学生有30个回答。所考虑的两个结局是受试者的积极情绪以及他们感到疲惫和无聊的程度。结果表明,结局的WS关联为负,并与几个协变量显著相关。两个结局的BS和WS方差均具有异质性,且随机尺度效应的方差显著不为零。

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