Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/65375
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dc.contributor.authorPeró, Maribel-
dc.contributor.authorGuàrdia-Olmos, Joan, 1958--
dc.date.accessioned2015-05-05T13:31:44Z-
dc.date.available2015-05-05T13:31:44Z-
dc.date.issued2013-
dc.identifier.issn0211-2159-
dc.identifier.urihttp://hdl.handle.net/2445/65375-
dc.description.abstractIn the current study, we evaluated various robust statistical methods for comparing two independent groups. Two scenarios for simulation were generated: one of equality and another of population mean differences. In each of the scenarios, 33 experimental conditions were used as a function of sample size, standard deviation and asymmetry. For each condition, 5000 replications per group were generated. The results obtained by this study show an adequate type error I rate but not a high power for the confidence intervals. In general, for the two scenarios studied (mean population differences and not mean population differences) in the different conditions analysed, the Mann-Whitney U-test demonstrated strong performance, and a little worse the t-test of Yuen-Welch.-
dc.format.extent18 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoeng-
dc.publisherUniversitat de València-
dc.relation.isformatofReproducció del document publicat a: https://www.uv.es/psicologica/articulos2.13/15Pero.pdf-
dc.relation.ispartofPsicologica, 2013, vol. 34, num. 2, p. 407-424-
dc.rights(c) Peró, Maribel et al., 2013-
dc.sourceArticles publicats en revistes (Psicologia Social i Psicologia Quantitativa)-
dc.subject.classificationEstadística robusta-
dc.subject.otherRobust statistics-
dc.titleThe adequacy of different robust statistical tests in comparing two independent groups-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.identifier.idgrec624897-
dc.date.updated2015-05-05T13:31:45Z-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
Appears in Collections:Articles publicats en revistes (Psicologia Social i Psicologia Quantitativa)

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