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

机译:双变量混合效应位置规模模型及其在生态矩评估中的应用

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摘要

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 9th and 10th 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.
机译:提出了一个双变量混合效应位置尺度模型,用于估计两个连续结果的均值,方差和协方差。联合对两个结果进行建模可以检查结果之间的BS和WS关联,以及关联是否与协变量相关。 BS和WS效应的方差-协方差矩阵根据协变量建模,解释了BS和WS的异质性。所提出的模型放宽了对受试者内部(WS)和受试者之间(BS)方差的均匀性的假设。此外,通过包括随机尺度效应来扩展WS方差模型。来自青少年吸烟自然史研究的数据用于说明。来自第9级和第10级的461名学生在连续7天中随机提示他们的情绪。这样就产生了14,105条提示,每名学生平均得到30条回复。考虑的两个结果是受试者的积极影响,以及他们感到疲倦和无聊的程度。结果显示,WS与结果的关联为负,并且与几个协变量显着关联。两种结果的BS和WS方差均不相同,随机标度影响的方差显着不同于零。

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