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.author Borkowf, Craig B. dc.contributor.author Gail, Mitchell H. dc.contributor.author Carroll, Raymond J. dc.contributor.author Gill, Richard D. dc.date.accessioned 2017-06-15T22:09:43Z dc.date.available 2017-06-15T22:09:43Z dc.date.created 2006-05-19 dc.date.issued 1997-01-13 dc.identifier.issn 1436-1086 dc.identifier.uri http://edoc.hu-berlin.de/18452/4452 dc.description.abstract Epidemiologists 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.iso eng dc.publisher Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät dc.rights.uri http://rightsstatements.org/vocab/InC/1.0/ dc.subject Agreement eng dc.subject bivariate sample quantile distribution eng dc.subject contingency table eng dc.subject kappa statistic eng dc.subject sample quantile eng dc.subject.ddc 330 Wirtschaft dc.title Analyzing bivariate continuous data that have been grouped into categories defined by Sample Quantiles of the Marginal Distributions dc.type book dc.identifier.urn urn:nbn:de:kobv:11-10063752 dc.identifier.doi http://dx.doi.org/10.18452/3800 dc.subject.dnb 17 Wirtschaft local.edoc.container-title Sonderforschungsbereich 373: Quantification and Simulation of Economic Processes local.edoc.pages 22 local.edoc.type-name Buch local.edoc.container-type series local.edoc.container-type-name Schriftenreihe local.edoc.container-volume 1997 local.edoc.container-issue 15 local.edoc.container-year 1997 local.edoc.container-erstkatid 2135319-0