Pairwise multiple comparisons: New yardstick, new results

dc.contributor.authorCribbie, Robert
dc.date.accessioned2018-06-05T01:15:01Z
dc.date.available2018-06-05T01:15:01Z
dc.date.issued2003
dc.description.abstractBehavioral science researchers often wish to compare the means of several treatment conditions on a specific dependent measure. The author used a Monte Carlo study to compare familywise error controlling multiple comparison procedures (MCPs; Tukey, Bonferroni) with MCPs that were not developed to control the familywise error rate on the probability of correctly identifying the true underlying population mean configuration (true model rate). Recently proposed MCPs that are not intended to control the familywise error rate had consistently larger true model rates than did familywise error controlling MCPs. Furthermore, of the familywise error controlling MCPs investigated, the popular Tukey and Bonferroni MCPs had consistently lower true model rates than did other familywise error controlling MCPs.en_US
dc.description.sponsorshipSocial Sciences and Humanities Research Council
dc.identifier.citationCribbie, R. A. (2003). Pairwise multiple comparisons: New yardstick, new results. Journal of Experimental Education, 71, 251-265. doi: 10.1080/00220970309602065
dc.identifier.urihttp://dx.doi.org/10.1080/00220970309602065en_US
dc.identifier.urihttp://hdl.handle.net/10315/34617
dc.language.isoenen_US
dc.publisherAmerican Psychological Associationen_US
dc.rights.articlehttp://psycnet.apa.org/record/2003-05800-002
dc.subjectfalse discovery rateen_US
dc.subjectmodel testingen_US
dc.subjectmultiple comparison proceduresen_US
dc.subjecttrue model rateen_US
dc.titlePairwise multiple comparisons: New yardstick, new results
dc.typeArticleen_US

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