Mixed-Effects Models for Cognitive Development Researchers

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)307-340
Number of pages34
JournalJournal of Cognition and Development
Issue number3
StatePublished - 2023

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Developmental and Educational Psychology
  • Psychiatry and Mental health


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