{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T13:14:46Z","timestamp":1762866886354,"version":"3.37.3"},"reference-count":20,"publisher":"Wiley","issue":"23","license":[{"start":{"date-parts":[[2016,5,30]],"date-time":"2016-05-30T00:00:00Z","timestamp":1464566400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2015,9,1]],"date-time":"2015-09-01T00:00:00Z","timestamp":1441065600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2016,10,15]]},"abstract":"<jats:p>The case\u2010control study is a common design for assessing the association between genetic exposures and a disease phenotype. Though association with a given (case\u2010control) phenotype is always of primary interest, there is often considerable interest in assessing relationships between genetic exposures and other (secondary) phenotypes. However, the case\u2010control sample represents a biased sample from the general population. As a result, if this sampling framework is not correctly taken into account, analyses estimating the effect of exposures on secondary phenotypes can be biased leading to incorrect inference. In this paper, we address this problem and propose a general approach for estimating and testing the population effect of a genetic variant on a secondary phenotype. Our approach is based on inverse probability weighted estimating equations, where the weights depend on genotype and the secondary phenotype. We show that, though slightly less efficient than a full likelihood\u2010based analysis when the likelihood is correctly specified, it is substantially more robust to model misspecification, and can out\u2010perform likelihood\u2010based analysis, both in terms of validity and power, when the model is misspecified. We illustrate our approach with an application to a case\u2010control study extracted from the Framingham Heart Study. Copyright \u00a9 2016 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/sim.6976","type":"journal-article","created":{"date-parts":[[2016,5,31]],"date-time":"2016-05-31T03:16:43Z","timestamp":1464664603000},"page":"4226-4237","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Robust analysis of secondary phenotypes in case\u2010control genetic association studies"],"prefix":"10.1002","volume":"35","author":[{"given":"Chuanhua","family":"Xing","sequence":"first","affiliation":[{"name":"Department of Biostatistics Boston University School of Public Health  Boston 02118 MA U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Janice","family":"M.\u00a0McCarthy","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Bioinformatics Duke University  Durham 27710 NC U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2871-3603","authenticated-orcid":false,"given":"Jos\u00e9e","family":"Dupuis","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Boston University School of Public Health  Boston 02118 MA U.S.A."},{"name":"National Heart, Lung and Blood Institute's Framingham Heart Study  Framingham 01702 MA U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"L.","family":"Adrienne\u00a0Cupples","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Boston University School of Public Health  Boston 02118 MA U.S.A."},{"name":"National Heart, Lung and Blood Institute's Framingham Heart Study  Framingham 01702 MA U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"James","family":"B.\u00a0Meigs","sequence":"additional","affiliation":[{"name":"General Medicine Division Massachusetts General Hospital  Boston 02114 MA U.S.A."},{"name":"Department of Medicine Harvard Medical School  Boston 02115 MA U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xihong","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Biostatistics Harvard University  Cambridge 01238 MA U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrew","family":"S.\u00a0Allen","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Bioinformatics Duke University  Durham 27710 NC U.S.A."},{"name":"Center for Human Genome Variation Duke University  Durham 27710 NC U.S.A."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2016,5,30]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1141634"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.140"},{"issue":"5829","key":"e_1_2_6_4_1","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.1126\/science.1142358","article-title":"Genome\u2010wide association analysis identifies loci for type 2 diabetes and triglyceride levels","volume":"316","author":"Richa S","year":"2007","journal-title":"Science"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.76"},{"key":"e_1_2_6_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.75"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.121"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng2121"},{"key":"e_1_2_6_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.122"},{"key":"e_1_2_6_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.3097"},{"key":"e_1_2_6_11_1","doi-asserted-by":"publisher","DOI":"10.1097\/EDE.0b013e318060d25c"},{"key":"e_1_2_6_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.20424"},{"key":"e_1_2_6_13_1","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwq332"},{"key":"e_1_2_6_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.20377"},{"key":"e_1_2_6_15_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2012.01052.x"},{"volume-title":"Semiparametric Theory and Missing Data","year":"2006","author":"Tsiatis AT","key":"e_1_2_6_16_1"},{"key":"e_1_2_6_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/66.3.403"},{"key":"e_1_2_6_18_1","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1080\/01621459.1996.10476940","article-title":"A semiparametric mixture approach to case\u2010control studies with errors in covariables","volume":"91","author":"Roeder K","year":"1996","journal-title":"Journal of the American Statistical Association"},{"key":"e_1_2_6_19_1","doi-asserted-by":"publisher","DOI":"10.1038\/ajh.2007.75"},{"key":"e_1_2_6_20_1","doi-asserted-by":"publisher","DOI":"10.1089\/met.2009.0074"},{"key":"e_1_2_6_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-3242-6"}],"container-title":["Statistics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fsim.6976","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/sim.6976","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,3]],"date-time":"2023-10-03T23:30:47Z","timestamp":1696375847000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/sim.6976"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,5,30]]},"references-count":20,"journal-issue":{"issue":"23","published-print":{"date-parts":[[2016,10,15]]}},"alternative-id":["10.1002\/sim.6976"],"URL":"https:\/\/doi.org\/10.1002\/sim.6976","archive":["Portico"],"relation":{},"ISSN":["0277-6715","1097-0258"],"issn-type":[{"type":"print","value":"0277-6715"},{"type":"electronic","value":"1097-0258"}],"subject":[],"published":{"date-parts":[[2016,5,30]]}}}