Poster #12 - MultiSCED: A Tool for (Meta-)Analyzing Single-Case Experimental Data With Multilevel Modeling

• In Event: 47.099 - MTCC Poster Session 11
  In Poster Session: 47.099-1 - Division D Section 2 Statistical Theory and Quantitative Methodologies

Abstract

The MultiSCED web application (https://ppw.kuleuven.be/single-case/MultiSCED) has been developed to assist applied researchers in behavioral sciences to apply multilevel modeling to quantitatively summarize single-case experimental design (SCED) studies. The application offers a user-friendly point-and-click interface embedded within R. In this paper, we offer a brief introduction to MultiSCED, explaining how to define and estimate the relevant multilevel models and how to interpret the results numerically and graphically. The use of the application is illustrated through a re-analysis of an existing meta-analytic dataset (Shogren, Faggella-Luby, Bae, & Wehmeyer, 2004). By guiding applied researchers through MultiSCED, we aim to make the use of the multilevel modeling technique for combining SCED data across cases and across studies more comprehensible and accessible.

Authors

• Lies Declercq, KU Leuven

• Wilfried Cools, Catholic University of Leuven

• Tasha Beretvas, The University of Texas at Austin

• Mariola Moeyaert, University at Albany

• John M. Ferron, University of South Florida

• Wim Van den Noortgate, KU Leuven