Evaluation of Treatment Effect Estimates in Single-Case Experimental Research: Comparison of Twelve Overlap Methods and Visual Analysis

Autor/inn/en	Yucesoy-Ozkan, Serife; Rakap, Salih; Gulboy, Emrah
Titel	Evaluation of Treatment Effect Estimates in Single-Case Experimental Research: Comparison of Twelve Overlap Methods and Visual Analysis
Quelle	In: British Journal of Special Education, 47 (2020) 1, S.67-87 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Yucesoy-Ozkan, Serife) ORCID (Rakap, Salih) ORCID (Gulboy, Emrah)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0952-3383
DOI	10.1111/1467-8578.12294
Schlagwörter	Effect Size; Graphs; Data Analysis; Computation; Evaluation Methods; Research Methodology + Suchen Sie Ihr Suchwort? Grafische Darstellung; Auswertung; Research method; Forschungsmethode
Abstract	The purpose of this study was to compare 12 commonly-used nonoverlap methods with each other and with the results of visual analysis. Data were obtained from 25 studies focused on embedded instruction and schema-based instruction and included a total of 101 graphs. Treatment effect estimates using 12 nonoverlap methods were calculated for each graph by hand or using an online calculator. Five experts conducted visual analysis of each graph. Results showed that strong agreements existed between visual analysis and PND, Tau[subscript NOVLAP] and Tau-U when raw data were analysed, and PND, PNCD and PEM-T when categorised data were analysed. Of the 12 methods investigated, PND had the highest agreement rate with visual analysis, followed by PEM-T, PAND, PNCD, IRD, NAP and Tau[subscript NOVLAP]. Overall, visual analysis appeared to be more conservative, as most nonoverlap methods overestimated the treatment effect. Additional research is needed to replicate and potentially validate the findings of this study. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2022/1/01