Using the dual-criteria methods to supplement visual inspection: An analysis of nonsimulated data
dc.contributor.author | Lanovaz, Marc | |
dc.contributor.author | Huxley, Sarah C. | |
dc.contributor.author | Dufour, Marie-Michèle | |
dc.date.accessioned | 2018-02-26T15:34:40Z | |
dc.date.available | NO_RESTRICTION | fr |
dc.date.available | 2018-02-26T15:34:40Z | |
dc.date.issued | 2017 | |
dc.identifier.uri | http://hdl.handle.net/1866/19841 | |
dc.publisher | Wiley | |
dc.subject | Data analysis | fr |
dc.subject | Dual-criteria method | fr |
dc.subject | False positive | fr |
dc.subject | Single-case designs | fr |
dc.subject | Type I error | fr |
dc.title | Using the dual-criteria methods to supplement visual inspection: An analysis of nonsimulated data | fr |
dc.type | Article | fr |
dc.contributor.affiliation | Université de Montréal. Faculté des arts et des sciences. École de psychoéducation | fr |
UdeM.statut | Professeur(e) / Professor | fr |
dc.identifier.doi | 10.1002/jaba.394 | |
dcterms.abstract | The purpose of our study was to examine the probability of observing false positives in non-simulated data using the dual-criteria methods. We extracted data from published studies to produce a series of 16,927 datasets and then assessed the proportion of false positives for various phase lengths. Our results indicate that collecting at least 3 data points in the first phase (Phase A) and at least 5 data points in the second phase (Phase B) is generally sufficient to produce acceptable levels of false positives. | fr |
dcterms.alternative | Dual-criteria methods 1 | fr |
dcterms.isPartOf | urn:ISSN:0021-8855 | |
dcterms.isPartOf | urn:ISSN:1938-3703 | |
dcterms.language | eng | fr |
UdeM.VersionRioxx | Version acceptée / Accepted Manuscript | fr |
oaire.citationTitle | Journal of applied behavior analysis | |
oaire.citationVolume | 50 | |
oaire.citationIssue | 3 | |
oaire.citationStartPage | 662 | |
oaire.citationEndPage | 667 |
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