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混合效应模型如何增进我们对学习和记忆的理解,并改善临床和教育实践。

How Mixed-Effects Modeling Can Advance Our Understanding of Learning and Memory and Improve Clinical and Educational Practice.

机构信息

Center for Childhood Deafness, Language, and Learning Research, Boys Town National Research Hospital, Omaha, NE.

出版信息

J Speech Lang Hear Res. 2019 Mar 25;62(3):507-524. doi: 10.1044/2018_JSLHR-L-ASTM-18-0240.

Abstract

Purpose A key goal of researchers, clinicians, and educators within the fields of speech, language, and hearing sciences is to support the learning and memory of others. To do so, they consider factors relevant to the individual, the material to be learned, and the training strategy that can maximize learning and retention. Statistical methods typically used within these fields are inadequate for identifying the complex relationships between these factors and are ill equipped to account for variability across individuals when identifying these relationships. Specifically, traditional statistical methods are often inadequate for answering questions about special populations because samples drawn from these populations are usually small, highly variable, and skewed in distribution. Mixed-effects modeling provides advantages over traditional statistical techniques to answer complex questions while taking into account these common characteristics of special populations. Method and Results Through 2 examples, I illustrate advantages of mixed-effects modeling in answering questions about learning and memory and in supporting better translation of research to practice. I also demonstrate key similarities and differences between analysis of variance, regression analyses, and mixed-effects modeling. Finally, I explain 3 additional advantages of using mixed-effects modeling to understand the processes of learning and memory: the means to account for missing data, assess the contribution of variations in delay intervals, and model nonlinear relationships between factors. Conclusions Through mixed-effects modeling, researchers can disseminate accurate information about learning and memory to clinicians and educators. In turn, through enhanced statistical literacy, clinicians and educators can apply research findings to practice with confidence. Overall, mixed-effects modeling is a powerful tool to improve the outcomes of the individuals that researchers and practitioners serve within the fields of speech, language, and hearing sciences.

摘要

目的

言语、语言和听力科学领域的研究人员、临床医生和教育工作者的一个关键目标是支持他人的学习和记忆。为此,他们会考虑与个体、要学习的材料以及能够最大程度地促进学习和保留的培训策略相关的因素。这些领域内通常使用的统计方法不足以确定这些因素之间的复杂关系,也无法在确定这些关系时充分考虑个体之间的变异性。具体来说,传统的统计方法通常不足以回答有关特殊人群的问题,因为从这些人群中抽取的样本通常数量较少、高度可变且分布偏斜。混合效应模型通过考虑特殊人群的这些常见特征,为回答复杂问题提供了优于传统统计技术的优势。

方法和结果

通过 2 个示例,我说明了混合效应模型在回答学习和记忆问题以及支持更好地将研究转化为实践方面的优势。我还展示了方差分析、回归分析和混合效应模型之间的关键相似点和不同点。最后,我解释了使用混合效应模型来理解学习和记忆过程的另外 3 个优势:处理缺失数据的方法、评估延迟间隔变化的贡献以及对因素之间非线性关系建模的能力。

结论

通过混合效应模型,研究人员可以向临床医生和教育工作者传播有关学习和记忆的准确信息。反过来,通过增强统计素养,临床医生和教育工作者可以有信心地将研究结果应用于实践。总体而言,混合效应模型是一种强大的工具,可以改善言语、语言和听力科学领域的研究人员和从业者所服务的个体的结果。

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