Twice random, once mixed: applying mixed models to simultaneously analyze random effects of language and participants

DP Janssen

Research output: Contribution to journalArticleScientificpeer-review

27 Citations (Scopus)
67 Downloads (Pure)

Abstract

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.

Original languageEnglish
Pages (from-to)232-247
Number of pages16
JournalBehaviour Research Methods
Volume44
Issue number1
DOIs
Publication statusPublished - 2012

Keywords

  • ANOVA
  • Hierarchical linear modeling
  • Item effects
  • Language as a fixed effect fallacy
  • Mixed models

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