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A primer for using multilevel models to meta‐analyze single case design data with AB phases
Author(s) -
Becraft Jessica L.,
Borrero John C.,
Sun Shuyan,
McKenzie Anlara A.
Publication year - 2020
Publication title -
journal of applied behavior analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 76
eISSN - 1938-3703
pISSN - 0021-8855
DOI - 10.1002/jaba.698
Subject(s) - meta analysis , sort , value (mathematics) , primer (cosmetics) , computer science , experimental data , data mining , data science , management science , psychology , information retrieval , machine learning , statistics , mathematics , medicine , chemistry , organic chemistry , economics
Meta‐analytic methods provide a way to synthesize data across treatment evaluation studies. However, these well‐accepted methods are infrequent with behavior analytic studies. Multilevel models may be a promising method to meta‐analyze single‐case data. This technical article provides a primer for how to conduct a multilevel model with single‐case designs with AB phases using data from the differential‐reinforcement‐of‐low‐rate behavior literature. We provide details, recommendations, and considerations for searching for appropriate studies, organizing the data, and conducting the analyses. All data sets are available to allow the reader to follow along with this primer. The purpose of this technical article is to minimally equip behavior analysts to complete a meta‐analysis that will summarize a current state of affairs as it relates to the science of behavior analysis and its practice. Moreover, we aim to demonstrate the value of analyses of this sort for behavior analysis.