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dc.contributor.authorDitzhaus, Marc-
dc.contributor.authorFried, Roland-
dc.contributor.authorPauly, Markus-
dc.date.accessioned2021-03-05T08:27:58Z-
dc.date.available2021-03-05T08:27:58Z-
dc.date.issued2021-02-24-
dc.identifier.urihttp://hdl.handle.net/2003/40061-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-21941-
dc.description.abstractPopulation means and standard deviations are the most common estimands to quantify effects in factorial layouts. In fact, most statistical procedures in such designs are built toward inferring means or contrasts thereof. For more robust analyses, we consider the population median, the interquartile range (IQR) and more general quantile combinations as estimands in which we formulate null hypotheses and calculate compatible confidence regions. Based upon simultaneous multivariate central limit theorems and corresponding resampling results, we derive asymptotically correct procedures in general, potentially heteroscedastic, factorial designs with univariate endpoints. Special cases cover robust tests for the population median or the IQR in arbitrary crossed one-, two- and higher-way layouts with potentially heteroscedastic error distributions. In extensive simulations, we analyze their small sample properties and also conduct an illustrating data analysis comparing children’s height and weight from different countries.en
dc.language.isoende
dc.relation.ispartofseriesTEST;30-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectBirth cohortsen
dc.subjectIQRen
dc.subjectMain and interaction effectsen
dc.subjectMedianen
dc.subjectPermutation testsen
dc.subject.ddc310-
dc.titleQANOVA: quantile-based permutation methods for general factorial designsen
dc.typeTextde
dc.type.publicationtypearticleen
dc.subject.rswkStatistischer Testde
dc.subject.rswkNichtparametrische Schätzungde
dc.subject.rswkResamplingde
dcterms.accessRightsopen access-
eldorado.secondarypublicationtruede
eldorado.secondarypublication.primaryidentifierhttps://doi.org/10.1007/s11749-021-00758-yde
eldorado.secondarypublication.primarycitationDitzhaus, M., Fried, R. & Pauly, M. QANOVA: quantile-based permutation methods for general factorial designs. TEST 30, 960–979 (2021). https://doi.org/10.1007/s11749-021-00758-yde
Appears in Collections:Institut für Mathematische Statistik und industrielle Anwendungen

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