Social and behavioral scientists are increasingly interested the dynamics of the processes they study. Despite the wide array of processes studied, a fairly narrow set of models are applied to characterize dynamics within these processes. For social and behavioral research to take the next step in modeling dynamics, a wider variety of models need to be considered. The reservoir model is one model of psychological regulation that helps expand the models available (Deboeck & Bergeman, 2013). The present article implements the Bayesian reservoir model for both single time series and multilevel data. Simulation 1 compares the performance of the original version of the reservoir model fit using structural equation modeling (Deboeck & Bergeman, 2013) to the proposed Bayesian estimation approach. Simulation 2 expands this to a multilevel data scenario and compares this to the single-level version. The Bayesian estimation approach performs substantially better than the original estimation approach and produces low-bias estimates even with time series as short as 25 observations. Combining Bayesian estimation with a multilevel modeling approach allows for relatively unbiased estimation with sample sizes as small as 15 individuals and/or with time series as short as 15 observations. Finally, a substantive example is presented that applies the Bayesian reservoir model to perceived stress, examining how the model parameters relate to psychological variables commonly expected to relate to resilience. The current expansion of the reservoir model demonstrates the benefits of leveraging the combined strengths of Bayesian estimation and multilevel modeling, with new dynamic models that have been tailored to match the process of psychological regulation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

中文翻译：

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心理调节的贝叶斯水库模型。


社会和行为科学家对他们研究的过程的动态越来越感兴趣。尽管研究了各种各样的过程，但应用了相当有限的一组模型来表征这些过程中的动力学。为了使社会和行为研究在动力学建模方面迈出下一步，需要考虑更广泛的模型。水库模型是一种心理调节模型，有助于扩展可用模型（Deboeck & Bergeman，2013）。本文针对单时间序列和多级数据实现了贝叶斯油藏模型。模拟 1 将使用结构方程建模（Deboeck & Bergeman，2013）的原始版本的储层模型拟合性能与所提出的贝叶斯估计方法进行了比较。模拟 2 将其扩展到多级数据场景，并将其与单级版本进行比较。贝叶斯估计方法的性能明显优于原始估计方法，即使时间序列短至 25 个观测值，也能产生低偏差估计。将贝叶斯估计与多级建模方法相结合，可以实现相对无偏的估计，样本量小至 15 个个体和/或时间序列短至 15 个观测值。最后，提出了一个实质性示例，将贝叶斯水库模型应用于感知压力，检查模型参数如何与通常预期与复原力相关的心理变量相关。当前水库模型的扩展证明了利用贝叶斯估计和多级建模的综合优势以及专为匹配心理调节过程而定制的新动态模型的好处。 （PsycInfo 数据库记录 (c) 2024 APA，保留所有权利）。