Mixed-effects models are becoming common in psychological science. Although they have many desirable features, there is still untapped potential. It is customary to view homogeneous variance as an assumption to satisfy. We argue to move beyond that perspective, and to view modeling within-person variance as an opportunity to gain a richer understanding of psychological processes. The technique to do so is based on the mixed-effects location scale model that can simultaneously estimate mixed-effects submodels to both the mean (location) and within-person variance (scale). We develop a framework that goes beyond assessing the submodels in isolation of one another and introduce a novel Bayesian hypothesis test for mean-variance correlations in the distribution of random effects. We first present a motivating example, which makes clear how the model can characterize mean-variance relations. We then apply the method to reaction times (RTs) gathered from 2 cognitive inhibition tasks. We find there are more individual differences in the within-person variance than the mean structure, as well as a complex web of structural mean-variance relations. This stands in contrast to the dominant view of within-person variance (i.e., "noise"). The results also point toward paradoxical within-person, as opposed to between-person, effects: several people had slower and less variable incongruent responses. This contradicts the typical pattern, wherein larger means tend to be associated with more variability. We conclude with future directions, spanning from methodological to theoretical inquires, that can be answered with the presented methodology. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

中文翻译：

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表面之下：挖掘人体内的变异性以及与贝叶斯混合模型的平均关系。


混合效应模型在心理科学中变得越来越普遍。尽管它们具有许多理想的功能，但仍有尚未开发的潜力。人们习惯上将齐次方差视为需要满足的假设。我们主张超越这种观点，并将人体内差异建模视为获得对心理过程更丰富理解的机会。这样做的技术基于混合效应位置尺度模型，该模型可以同时估计平均（位置）和人内方差（尺度）的混合效应子模型。我们开发了一个框架，该框架超越了单独评估子模型的范围，并引入了一种新颖的贝叶斯假设检验，用于随机效应分布中的均值方差相关性。我们首先提出一个激励性的例子，它清楚地表明了模型如何表征均值-方差关系。然后，我们将该方法应用于从 2 个认知抑制任务中收集的反应时间 (RT)。我们发现人内方差比均值结构存在更多的个体差异，并且结构均值-方差关系的复杂网络。这与人内差异（即“噪音”）的主流观点形成鲜明对比。研究结果还指出，与人与人之间相反，人与人之间存在着矛盾的效应：一些人的不一致反应较慢且变化较小。这与典型的模式相矛盾，其中较大的均值往往与更多的变异性相关。我们总结了从方法论到理论探究的未来方向，这些方向可以用所提出的方法来回答。 （PsycInfo 数据库记录 (c) 2020 APA，保留所有权利）。