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30.075 - The Meta-Analysis of Single-Subject Experimental Design Data: Methodological Challenges and Approaches
Fri, April 28, 12:25 to 1:55pm, Henry B. Gonzalez Convention Center, Floor: Meeting Room Level, Room 221 DSession Type: Structured Poster Session
Abstract
Single-subject experimental designs (SSEDs) are increasingly used in educational research to evaluate intervention effects. With the increase of published SSED studies, also the interest for the meta-analysis of SSED studies has grown. The aim of the session is to share findings of recent methodological research on the meta-analysis of SSED data and promote further discussion and collaboration between research teams on remaining challenges. This session consists of twelve posters, one giving a systematic overview of the way SSED studies were reviewed the last three decades, five focusing on the calculation of effect sizes and their precision, three on meta-analytic models for SSED data and three aimed at aiding researchers to set up reasonable SSED studies or meta-analyses.
Sub Unit
Chair
Papers
1. Review of Systematic Reviews and Meta-Analyses of Single-Subject Experimental Studies - Laleh Jamshidi, KU Leuven; Mieke Heyvaert, Katholieke Universiteit Leuven; Wim Van den Noortgate, Katholieke Universiteit Leuven
2. Estimating Instantaneous and Maximum Treatment Effect Sizes for Nonlinear Treatment-Phase Trajectories in Single-Subject Experimental Design Studies - Christopher Runyon, The University of Texas - Austin; Susan Natasha Beretvas, The University of Texas - Austin
3. Estimation of Effect Size in Single-Case Designs From Overlap - David M. Rindskopf, City University of New York
4. Bias and Precision of Within- and Between-Series Effect Estimates in the Meta-Analysis of Multiple Baseline Studies - Seang-hwane Joo, University of South Florida; Yan Wang, University of South Florida; John M. Ferron, University of South Florida
5. Response Ratio Effect Sizes for Single-Case Designs With Behavioral Outcome Measures - James Eric Pustejovsky, The University of Texas - Austin
6. Confidence Intervals for Single-Case Effect Size Measures Based on Randomization Test Inversion - Bart Michiels, KU Leuven; Mieke Heyvaert, Katholieke Universiteit Leuven; Ann Meulders, KU Leuven; Patrick Onghena, KU Leuven
7. Intervention Analysis Models for Single-Case Designs - Daniel Swan, The University of Texas - Austin; James Eric Pustejovsky, The University of Texas - Austin
8. A Quasi-Likelihood/Generalized Estimating Equation Approach to Count Outcomes in Single-Case Experimental Designs - Mariola Moeyaert, University at Albany; Jay Verkuilen, City University of New York
9. Analyzing Single-Case Experimental Count Data Using the Linear Mixed Effects Model: A Simulation Study - Lies Declercq, KU Leuven; Wim Van den Noortgate, Katholieke Universiteit Leuven
10. A Demonstration and Evaluation Using Single-Subject Experimental Design Studies Data - Daniel Peche Gonzalez, The University of Texas - Austin; Susan Natasha Beretvas, The University of Texas - Austin; Christopher Runyon, The University of Texas - Austin
11. The Power to Test Moderator Effects in Multilevel Modeling of Single-Case Data - Diana Akhmedjanova, University at Albany - SUNY; David Bogin, University at Albany - SUNY; Mariola Moeyaert, University at Albany
12. Waiting for Baselines to Stabilize: Consequences of Response-Guided Experimentation on Meta-Analyses of Single-Case Studies - John M. Ferron, University of South Florida; Seang-hwane Joo, University of South Florida