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1997-01-13Buch DOI: 10.18452/3800
Analyzing bivariate continuous data that have been grouped into categories defined by Sample Quantiles of the Marginal Distributions
dc.contributor.authorBorkowf, Craig B.
dc.contributor.authorGail, Mitchell H.
dc.contributor.authorCarroll, Raymond J.
dc.contributor.authorGill, Richard D.
dc.date.accessioned2017-06-15T22:09:43Z
dc.date.available2017-06-15T22:09:43Z
dc.date.created2006-05-19
dc.date.issued1997-01-13
dc.identifier.issn1436-1086
dc.identifier.urihttp://edoc.hu-berlin.de/18452/4452
dc.description.abstractEpidemiologists sometimes study the association between two measures of exposure on the same subjects by grouping the data into categories that are defined by sample quantiles of the two marginal distributions. Although such grouped data are presented in a twoway contingency table, the cell counts in this table do not have a multinomial distribution. We use the term “bivariate quantile distribution” (BQD) to describe the joint distribution of counts in such a table. Blomqvist (1950) gave an exact BQD theory for the case of only 4 categories based on division at the sample medians. The asymptotic theory he presented was not valid, however, except in special cases. We present a valid asymptotic theory for arbitrary numbers of categories and apply this theory to construct confidence intervals for the kappa statistic. We show by simulations that the confidence interval procedures we propose have near nominal coverage for sample sizes exceeding 90, both for 2 x 2 and 3 x 3 tables. These simulations also illustrate that the asymptotic theory of Blomqvist (1950) and the methods given by Fleiss, Cohen and Everitt (1969) for multinomial sampling can yield subnominal coverage for BQD data, although in some cases the coverage for these procedures is near nominal levels.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectAgreementeng
dc.subjectbivariate sample quantile distributioneng
dc.subjectcontingency tableeng
dc.subjectkappa statisticeng
dc.subjectsample quantileeng
dc.subject.ddc330 Wirtschaft
dc.titleAnalyzing bivariate continuous data that have been grouped into categories defined by Sample Quantiles of the Marginal Distributions
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10063752
dc.identifier.doihttp://dx.doi.org/10.18452/3800
dc.subject.dnb17 Wirtschaft
local.edoc.container-titleSonderforschungsbereich 373: Quantification and Simulation of Economic Processes
local.edoc.pages22
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume1997
local.edoc.container-issue15
local.edoc.container-year1997
local.edoc.container-erstkatid2135319-0

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