Mixed-Effects Models for Cognitive Development Researchers

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 devel...

Full description

Saved in:
Bibliographic Details
Published inJournal of cognition and development Vol. 24; no. 3; pp. 307 - 340
Main Authors Muradoglu, Melis, Cimpian, Joseph R., Cimpian, Andrei
Format Journal Article
LanguageEnglish
Published Philadelphia Routledge 27.05.2023
Taylor & Francis Ltd
Subjects
Cognitive ability
Cognitive Development
Measurement
Programming Languages
Psychologists
Research Methodology
Scientific Research
Troubleshooting
Online AccessGet full text

Cover

More Information
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1524-8372
1532-7647
DOI:10.1080/15248372.2023.2176856