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dc.contributor.authorTaylor, Tessa
dc.contributor.authorLanovaz, Marc
dc.date.accessioned2022-05-02T12:25:38Z
dc.date.availableNO_RESTRICTIONfr
dc.date.available2022-05-02T12:25:38Z
dc.date.issued2022-04-27
dc.identifier.urihttp://hdl.handle.net/1866/26631
dc.publisherWileyfr
dc.rightsCe document est mis à disposition selon les termes de la Licence Creative Commons Paternité 4.0 International. / This work is licensed under a Creative Commons Attribution 4.0 International License.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/deed.fr
dc.subjectArtificial intelligencefr
dc.subjectConservative dual criteriafr
dc.subjectInterrater agreementfr
dc.subjectMachine learningfr
dc.subjectVisual inspectionfr
dc.titleAgreement between visual inspection and objective analysis methods : a replication and extensionfr
dc.typeArticlefr
dc.contributor.affiliationUniversité de Montréal. Faculté des arts et des sciences. École de psychoéducationfr
dc.identifier.doi10.1002/jaba.921
dcterms.abstractBehavior 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.fr
dcterms.isPartOfurn:ISSN:1938-3703fr
dcterms.languageengfr
dcterms.relationhttps://osf.io/2wgtu/fr
UdeM.ReferenceFournieParDeposantTaylor, T., & Lanovaz, M. J. (2022). Agreement between visual inspection and objective methods of analyses: A replication and extension. Journal of Applied Behavior Analysis. https://doi.org/10.1002/jaba.921fr
UdeM.VersionRioxxVersion publiée / Version of Recordfr
oaire.citationTitleJournal of applied behavior analysisfr


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Ce document est mis à disposition selon les termes de la Licence Creative Commons 
Paternité 4.0 International. / This work is licensed under a Creative Commons Attribution 4.0 
International License.
RightsCe document est mis à disposition selon les termes de la Licence Creative Commons Paternité 4.0 International. / This work is licensed under a Creative Commons Attribution 4.0 International License.

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