{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:25:14Z","timestamp":1740133514776,"version":"3.37.3"},"reference-count":17,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T00:00:00Z","timestamp":1676851200000},"content-version":"vor","delay-in-days":2184,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["CA53996","CA201207","ES17030","GM100573","HL121347","MH105857","HL130483"],"award-info":[{"award-number":["CA53996","CA201207","ES17030","GM100573","HL121347","MH105857","HL130483"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DMS-1106816"],"award-info":[{"award-number":["DMS-1106816"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Mathematics Research Promotion Center of the National Science Council of Taiwan"},{"name":"Japanese Ministry of Health, Labour and Welfare"},{"DOI":"10.13039\/100000015","name":"US Department of Energy","doi-asserted-by":"publisher","award":["DE-HS0000031"],"award-info":[{"award-number":["DE-HS0000031"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]},{"name":"RERF","award":["18-59"],"award-info":[{"award-number":["18-59"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,11,1]]},"abstract":"<jats:title>Summary<\/jats:title>\n               <jats:p>Observational epidemiological studies often confront the problem of estimating exposure\u2013disease relationships when the exposure is not measured exactly. We investigate exposure measurement error in excess relative risk regression, which is a widely used model in radiation exposure effect research. In the study cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies a generalized version of the classical additive measurement error model, but it may or may not have repeated measurements. In addition, an instrumental variable is available for individuals in a subset of the whole cohort. We develop a non-parametric correction estimator by using data from the subcohort and further propose a joint non-parametric correction estimator using all observed data to adjust for exposure measurement error. An optimal linear combination estimator of the joint non-parametric correction and non-parametric correction is further developed. The estimators proposed are non-parametric, which are consistent without imposing a covariate or error distribution, and are robust to heteroscedastic errors. Finite sample performance is examined via a simulation study. We apply the developed methods to data from the Radiation Effects Research Foundation, in which chromosome aberration is used to adjust for the effects of radiation dose measurement error on the estimation of radiation dose responses.<\/jats:p>","DOI":"10.1111\/rssb.12230","type":"journal-article","created":{"date-parts":[[2017,2,28]],"date-time":"2017-02-28T04:37:54Z","timestamp":1488256674000},"page":"1583-1599","source":"Crossref","is-referenced-by-count":4,"title":["Joint Non-Parametric Correction Estimator for Excess Relative Risk Regression in Survival Analysis with Exposure Measurement Error"],"prefix":"10.1093","volume":"79","author":[{"given":"Ching-Yun","family":"Wang","sequence":"first","affiliation":[{"name":"Fred Hutchinson Cancer Research Center , Seattle , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Harry","family":"Cullings","sequence":"additional","affiliation":[{"name":"Radiation Effects Research Foundation , Hiroshima , Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Song","sequence":"additional","affiliation":[{"name":"University of Georgia , Athens , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kenneth J.","family":"Kopecky","sequence":"additional","affiliation":[{"name":"Fred Hutchinson Cancer Research Center , Seattle , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2017,2,27]]},"reference":[{"key":"2023022101103540900_rssb12230-cit-0001","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/S0378-3758(97)00108-0","article-title":"Unbiased scores in proportional hazards regression with covariate measurement error","volume":"67","author":"Buzas","year":"1998","journal-title":"J. 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