Twice random, once mixed: Applying mixed models to simultaneously analyze random effects of language and participants
Twice random, once mixed: Applying mixed models to simultaneously analyze random effects of language and participants
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DOI：
10.3758/s13428-011-0145-1
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发表时间：
2012-03-01
影响因子：
5.4
通讯作者：
Janssen, Dirk P.
中科院分区：
文献类型：
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作者：
Janssen, Dirk P.
使用语言刺激的心理学家，心理语言学家和其他研究人员已经挣扎了30多年，即如何分析包含两个交叉随机效应（项目和参与者）的实验数据的问题。经典方差分析不适用；已经提出了替代方案，但未能抓住替代方案，并且使用两个近似值（称为F（1）和F（2））的统计学上不令人满意的程序已成为标准。使用混合模型分析的简单而优雅的解决方案已有15年了，统计软件的最新改进使混合模型分析广泛可用。本文的目的是通过提供简洁的实用介绍并为在最流行的统计包中进行分析的明确指示来增加混合模型的使用。本文还介绍了SPSS的DJMIX插件包，这使得输入模型并尽可能直接地报告其结果。
Psychologists, psycholinguists, and other researchers using language stimuli have been struggling for more than 30 years with the problem of how to analyze experimental data that contain two crossed random effects (items and participants). The classical analysis of variance does not apply; alternatives have been proposed but have failed to catch on, and a statistically unsatisfactory procedure of using two approximations (known as F (1) and F (2)) has become the standard. A simple and elegant solution using mixed model analysis has been available for 15 years, and recent improvements in statistical software have made mixed models analysis widely available. The aim of this article is to increase the use of mixed models by giving a concise practical introduction and by giving clear directions for undertaking the analysis in the most popular statistical packages. The article also introduces the djmixed add-on package for SPSS, which makes entering the models and reporting their results as straightforward as possible.