Agreement between Visual Inspection and Objective Analysis Methods: A Replication and Extension

Autor/inn/en	Taylor, Tessa; Lanovaz, Marc J.
Titel	Agreement between Visual Inspection and Objective Analysis Methods: A Replication and Extension
Quelle	In: Journal of Applied Behavior Analysis, 55 (2022) 3, S.986-996 (11 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Taylor, Tessa) ORCID (Lanovaz, Marc J.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0021-8855
DOI	10.1002/jaba.921
Schlagwörter	Visual Perception; Artificial Intelligence; Decision Making; Evaluators; Interrater Reliability; Graphs; Comparative Analysis; Applied Behavior Analysis + Suchen Sie Ihr Suchwort? Visuelle Wahrnehmung; Künstliche Intelligenz; Decision-making; Entscheidungsfindung; Interrater-Reliabilität; Grafische Darstellung
Abstract	Behavior analysts typically rely on visual inspection of single-case experimental designs to make treatment decisions. However, visual inspection is subjective, which has led to the development of supplemental objective methods such as the conservative dual-criteria method. To replicate and extend a study conducted by Wolfe et al. (2018) on the topic, we examined agreement between the visual inspection of five raters, the conservative dual-criteria method, and a machine-learning algorithm (i.e., the support vector classifier) on 198 AB graphs extracted from clinical data. The results indicated that average agreement between the 3 methods was generally consistent. Mean interrater agreement was 84%, whereas raters agreed with the conservative dual-criteria method and the support vector classifier on 84% and 85% of graphs, respectively. Our results indicate that both objective methods produce results consistent with visual inspection, which may support their future use. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01