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