Meta-analysis of single-case experimental designs: An overview of current synthesis methods
About the Webcast
This webcast focusing on Meta-analysis of single-case experimental designs: An overview of current synthesis methods is sponsored by the Campbell Collaboration and kicks off the 2023 Campbell Webinar Series. The Center on Knowledge Translation for Disability and Rehabilitation Research (KTDRR) is co-sponsoring the event as part of its research synthesis webcast series.
The presentation will provide an overview of current state-of-the-art methodology in meta-analysis of single-case experimental designs (SCDs). SCDs are typically examining pre- versus post-treatment performance within a small sample of participants. The adoption of evidence-based practice calls for the synthesis of SCDs through meta-analysis. Considerable progress has been made in developing effect size (ES) estimation and aggregation methods for SCDs, including non-parametric procedures in addition to advanced regression and multi-level modeling techniques.
Most recent developments have also explored the combination of group and single case data in a single meta-analysis through compatible ES estimators. The presenter will provide an overview on contemporary approaches to ES estimation in SCDs and meaningful aggregation in systematic reviews and meta-analyses. Resources will be shared to guide applied researchers in the planning and implementation stages of research syntheses that involve SCD data.
View the Archive
This webcast aired live via the Zoom platform on February 7, 2023. The archive is available on YouTube at this link: https://youtu.be/bgQ1kO7JGdI
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About the Presenter
Mariola Moeyaert, PhD, MBA, is associate professor of statistics in the School of Education, University at Albany. She obtained her Ph.D. in Educational Statistics from the University of Leuven (Belgium) and worked as a Postdoctoral fellow at the Center of Advanced Study in Education at the City University of New York. She joined the faculty of Educational Psychology and Methodology, University at Albany, in the Fall of 2015. Dr. Moeyaert obtained the 2016 Anastasi Dissertation Award Division 5 of the American Psychological Association (innovative quantitative research methods).
Her major research interests and publications are in the field of multilevel analysis, meta-analysis, large-scale data analysis, and interrupted time series. She has (co)authored over 65 international publications, reporting about developments in educational research methodology (including several extensive simulation studies) and about applications of statistical models to educational data.
Dr. Moeyaert’s research related to multilevel meta-analysis of single-case design studies has been funded by three IES grants (R305D110024, Multilevel synthesis of single-case experimental data: Further developments and empirical validation; R305D150007, Multilevel modeling of single-subject experimental data: Handling data and design complexities; and R305D190022, Assessing generalizability and variability of single-case design effect sizes using multilevel modeling including moderators).
Oliver Wendt, PhD, is associate professor and chair of inclusive education in cognitive and emotional disabilities at the University of Potsdam, Germany. He also holds appointments as adjunct associate professor in the Department of Human Development and Family Sciences at Purdue University and as research associate with the Centre for Augmentative and Alternative Communication at the University of Pretoria in South Africa. Together with Joann Starks he serves as co-chair of the Campbell Disability Coordinating Group. His research lab develops interventions and technologies for individuals with severe autism and/or neurodevelopmental disorders. Dr. Wendt specializes in single-subject experimental designs and meta-analyses of these studies. He serves on the editorial boards of the American Journal of Speech-Language Pathology, Augmentative and Alternative Communication, Campbell Systematic Reviews, and Evidence-based Communication Assessment and Intervention.
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