ABSTRACT

Mixed-effects models are an analytic technique for modeling repeated measurement or nested data. This paper explains the logic of mixed-effects modeling and describes two examples of mixed-effects analyses using R. The intended audience of the paper is psychologists who specialize in cognitive development research. Therefore, the concepts and examples covered will focus primarily on repeated-measurement data resulting from studies in which participants respond to multiple items or trials. However, many of the concepts and examples we cover will likely be of use to readers outside this area of psychology. Finally, we discuss recommendations for dealing with practical challenges, suggest approaches for troubleshooting, and provide guidance on reporting results from mixed-effects models.

摘要

混合效应模型是一种用于对重复测量或嵌套数据进行建模的分析技术。本文解释了混合效应建模的逻辑，并描述了使用 R 进行混合效应分析的两个示例。本文的目标受众是专门从事认知发展研究的心理学家。因此，所涵盖的概念和示例将主要集中于参与者对多个项目或试验做出反应的研究中产生的重复测量数据。然而，我们介绍的许多概念和例子可能对心理学领域之外的读者有用。最后，我们讨论了处理实际挑战的建议，提出了故障排除方法，并提供了报告混合效应模型结果的指导。