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Innovative Methodologies and Systematic Reviews in Analyzing Single-Case Experimental Design Data
Sat, April 26, 5:10 to 6:40pm MDT (5:10 to 6:40pm MDT), The Colorado Convention Center, Floor: Terrace Level, Bluebird Ballroom Room 2ASession Type: Structured Poster Session
Abstract
The increasing emphasis on evidence-based practice in disciplines employing single-case experimental design (SCED) has driven methodological advancements in effect size estimation and analytic techniques. This has prompted methodologists to develop quantitative effect size measures and analysis techniques. This session presents ten research studies that introduce recent innovations and systematic reviews of the current methodological practices in SCED. Several studies introduce and examine methodological advances aimed at facilitating the use of statistical developments by applied researchers. Other studies provide systematic reviews of assessment and analysis in SCED studies, intending to guide methodologists in future directions. Additionally, some studies offer guidance to researchers on interpreting SCED effect sizes based on their choices of coding and effect size measures.
Sub Unit
Chair
Papers
A Methodological Review of Statistical Options for Analyzing Single-Case Studies (Poster 1) - John M. Ferron, University of South Florida; Megan Kirby, University of South Florida; Lodi Lipien, Florida Virtual School; Moses Muchiri Mohamed, University of South Florida; Courtney Howard-Kirby, University of South Florida
Systematic Review of Single-Case Designs to Identify Mediator Characteristics (Poster 2) - Mariola Moeyaert, University at Albany - SUNY; Joelle Fingerhut, Marist College; Milica Miocevic, McGill University; Matthew Valente, University of South Florida; Panpan Yang, Princeton University; Yaosheng Lou, University at Albany - SUNY
A Scoping Review of Quality Appraisal and Risk-of-Bias Assessment Tools for Single-Case Experimental Designs (Poster 3) - Oliver Wendt, University of Potsdam; Mariola Moeyaert, University at Albany - SUNY; Joelle Fingerhut, Marist College; Bridget T. Miller, University of South Carolina
Bayesian Zero-inflated Generalized Linear Mixed Model for Single Case Experimental Design (Poster 4) - Chendong Li, Texas A&M University; Haoran Li, University of Minnesota
Bayes Factor for Analyzing Single-Case Experimental Designs: The Case of Multiple-Baseline Design (Poster 5) - Tsuyoshi Yamada, Yokohama City University; Kensuke Okada, University of Tokyo
Variance Estimation in SCED Meta-analysis: Bootstrapping to the Rescue (Poster 6) - Wim Van den Noortgate, KU Leuven; Mariola Moeyaert, University at Albany - SUNY
Generalized Least Squares (GLS) transformation in analyzing Single-Case Experimental Design (Poster 7) - Chendong Li, Texas A&M University; Eunkyeng Baek, Texas A&M University; Wen Luo, Texas A&M University
Synthesis of Single-Case Design Mediation Effects using Two-Stage Multilevel Modeling (Poster 8) - Mariola Moeyaert, University at Albany - SUNY; Matthew Valente, University of South Florida; Milica Miocevic, McGill University; Sofía Isabel Maiz García, Instituto de Psicoterapia; Yaosheng Lou, University at Albany - SUNY
Conditional Versus Marginal Effects: Theoretical Foundation for Between-Case Incidence Rate Ratio with SCED Count Data (Poster 9) - Haoran Li, University of Minnesota; Wen Luo, Texas A&M University; Eunkyeng Baek, Texas A&M University
Coding ABAB Designs for Maximum Interpretability (Poster 10) - David M. Rindskopf, Graduate Center - CUNY