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dc.contributor.authorDing, AAen_US
dc.contributor.authorWang, WJen_US
dc.date.accessioned2014-12-08T15:39:29Z-
dc.date.available2014-12-08T15:39:29Z-
dc.date.issued2004-03-01en_US
dc.identifier.issn0162-1459en_US
dc.identifier.urihttp://hdl.handle.net/11536/26959-
dc.description.abstractThis article develops a nonparametric procedure for testing marginal independence based on bivariate current status data. Asymptotic properties of the proposed tests are derived, and their finite-sample performance is studied via simulations. The method is applied to analyze data from a community-based study of cardiovascular epidemiology in Taiwan.en_US
dc.language.isoen_USen_US
dc.subjectCochran-Mantel-Haenszel testen_US
dc.subjectepidemiologyen_US
dc.subjectinterval censoringen_US
dc.subjectlifetime dataen_US
dc.subjectnonparametric analysisen_US
dc.subjecttwo-by-two tableen_US
dc.titleTesting independence for bivariate current status dataen_US
dc.typeArticleen_US
dc.identifier.journalJOURNAL OF THE AMERICAN STATISTICAL ASSOCIATIONen_US
dc.citation.volume99en_US
dc.citation.issue465en_US
dc.citation.spage145en_US
dc.citation.epage155en_US
dc.contributor.department統計學研究所zh_TW
dc.contributor.departmentInstitute of Statisticsen_US
dc.identifier.wosnumberWOS:000220638200015-
dc.citation.woscount14-
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