{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T09:58:26Z","timestamp":1760954306976},"reference-count":7,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2001,3,12]],"date-time":"2001-03-12T00:00:00Z","timestamp":984355200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genetic Epidemiology"],"published-print":{"date-parts":[[2001,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>We compare the asymptotic relative efficiency (ARE) of different study designs for estimating gene and gene\u2010environment interaction effects using matched case\u2010control data. In the sampling schemes considered, cases are selected differentially based on their family history of disease. Controls are selected either from unrelated subjects or from among the case\u2019s unaffected siblings and cousins. Parameters are estimated using weighted conditional logistic regression, where the likelihood contributions for each subject are weighted by the fraction of cases sampled sharing the same family history. Results showed that compared to random sampling, over\u2010sampling cases with a positive family history increased the efficiency for estimating the main effect of a gene for sib\u2010control designs (103\u2013254% ARE) and decreased efficiency for cousin\u2010control and population\u2010control designs (68\u201394% ARE and 67\u201384% ARE, respectively). Population controls and random sampling of cases were most efficient for a recessive gene or a dominant gene with an relative risk less than 9. For estimating gene\u2010environment interactions, over\u2010sampling positive\u2010family\u2010history cases again led to increased efficiency using sib controls (111\u2013180% ARE) and decreased efficiency using population controls (68\u201387% ARE). Using case\u2010cousin pairs, the results differed based on the genetic model and the size of the interaction effect; biased sampling was only slightly more efficient than random sampling for large interaction effects under a dominant gene model (relative risk ratio = 8, 106% ARE). Overall, the most efficient study design for studying gene\u2010environment interaction was the case\u2010sib\u2010control design with over\u2010sampling of positive\u2010family\u2010history\u2010cases. Genet. Epidemiol. 20:316\u2013327, 2001. \u00a9 2001 Wiley\u2010Liss, Inc.<\/jats:p>","DOI":"10.1002\/gepi.3","type":"journal-article","created":{"date-parts":[[2002,8,25]],"date-time":"2002-08-25T21:46:18Z","timestamp":1030311978000},"page":"316-327","source":"Crossref","is-referenced-by-count":6,"title":["Stratified case sampling and the use of family controls"],"prefix":"10.1002","volume":"20","author":[{"given":"Kimberly D.","family":"Siegmund","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bryan","family":"Langholz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2001,3,12]]},"reference":[{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/75.1.11"},{"key":"e_1_2_1_3_1","first-page":"39","article-title":"Family\u2010based association studies","volume":"26","author":"Gauderman WJ","year":"1999","journal-title":"Monogr Natl Cancer Inst"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1214\/ss\/1032209663"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.jncimonographs.a024225"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.2307\/2532441"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.aje.a113266"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.aje.a009877"}],"container-title":["Genetic Epidemiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fgepi.3","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/gepi.3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,19]],"date-time":"2023-11-19T15:32:57Z","timestamp":1700407977000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/gepi.3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2001,3,12]]},"references-count":7,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2001,4]]}},"alternative-id":["10.1002\/gepi.3"],"URL":"https:\/\/doi.org\/10.1002\/gepi.3","archive":["Portico"],"relation":{},"ISSN":["0741-0395","1098-2272"],"issn-type":[{"value":"0741-0395","type":"print"},{"value":"1098-2272","type":"electronic"}],"subject":[],"published":{"date-parts":[[2001,3,12]]}}}