A primer for using multilevel models to meta-analyze single case design data with AB phases

被引:17
作者
Becraft, Jessica L. [1 ,2 ]
Borrero, John C. [3 ]
Sun, Shuyan [3 ]
McKenzie, Anlara A. [1 ,3 ]
机构
[1] Kennedy Krieger Inst, Columbia, MD USA
[2] Johns Hopkins Univ, Sch Med, Baltimore, MD 21218 USA
[3] UMBC, Baltimore, MD USA
关键词
differential-reinforcement-of-low-rate; hierarchical linear modeling; meta-analysis; multilevel model; quantitative review; single-case designs; DIFFERENCE EFFECT SIZE; REINFORCEMENT; INTERVENTION; METAANALYSES; DRL;
D O I
10.1002/jaba.698
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
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.
引用
收藏
页码:1799 / 1821
页数:23
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