{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T10:12:35Z","timestamp":1790763155319,"version":"4.1.0"},"reference-count":0,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2001,11,1]],"date-time":"2001-11-01T00:00:00Z","timestamp":1004572800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2001,11,1]]},"abstract":"<jats:title>Summary<\/jats:title>\n               <jats:p>A class of cohort sampling designs, including nested case\u2013control, case\u2013cohort and classical case\u2013control designs involving survival data, is studied through a unified approach using Cox\u2019s proportional hazards model. By finding an optimal sample reuse method via local averaging, a closed form estimating function is obtained, leading directly to the estimators of the regression parameters that are relatively easy to compute and are more efficient than some commonly used estimators in case\u2013cohort and nested case\u2013control studies. A semiparametric efficient estimator can also be found with some further computation. In addition, the class of sampling designs in this study provides a variety of sampling options and relaxes the restrictions of sampling schemes that are currently available.<\/jats:p>","DOI":"10.1111\/1467-9868.00313","type":"journal-article","created":{"date-parts":[[2003,3,12]],"date-time":"2003-03-12T19:37:12Z","timestamp":1047497832000},"page":"791-809","source":"Crossref","is-referenced-by-count":99,"title":["Generalized Case\u2013cohort Sampling"],"prefix":"10.1093","volume":"63","author":[{"given":"Kani","family":"Chen","sequence":"first","affiliation":[{"name":"Hong Kong University of Science and Technology , People\u2019s Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2002,4,21]]},"container-title":["Journal of the Royal Statistical Society Series B: Statistical Methodology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1111%2F1467-9868.00313","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/academic.oup.com\/jrsssb\/article-pdf\/63\/4\/791\/49590781\/jrsssb_63_4_791.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jrsssb\/article-pdf\/63\/4\/791\/49590781\/jrsssb_63_4_791.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T11:33:13Z","timestamp":1679484793000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jrsssb\/article\/63\/4\/791\/7083406"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2001,11,1]]},"references-count":0,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2002,4,21]]},"published-print":{"date-parts":[[2001,11,1]]}},"URL":"https:\/\/doi.org\/10.1111\/1467-9868.00313","relation":{},"ISSN":["1369-7412","1467-9868"],"issn-type":[{"value":"1369-7412","type":"print"},{"value":"1467-9868","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2001,11]]},"published":{"date-parts":[[2001,11,1]]}}}