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pubmed-article:11252619pubmed:dateCreated2001-3-16lld:pubmed
pubmed-article:11252619pubmed:abstractTextWe propose a conditional scores procedure for obtaining bias-corrected estimates of log odds ratios from matched case-control data in which one or more covariates are subject to measurement error. The approach involves conditioning on sufficient statistics for the unobservable true covariates that are treated as fixed unknown parameters. For the case of Gaussian nondifferential measurement error, we derive a set of unbiased score equations that can then be solved to estimate the log odds ratio parameters of interest. The procedure successfully removes the bias in naive estimates, and standard error estimates are obtained by resampling methods. We present an example of the procedure applied to data from a matched case-control study of prostate cancer and serum hormone levels, and we compare its performance to that of regression calibration procedures.lld:pubmed
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pubmed-article:11252619pubmed:authorpubmed-author:FreedmanL SLSlld:pubmed
pubmed-article:11252619pubmed:authorpubmed-author:CarrollR JRJlld:pubmed
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pubmed-article:11252619pubmed:authorpubmed-author:DorganJ FJFlld:pubmed
pubmed-article:11252619pubmed:authorpubmed-author:MidthuneD NDNlld:pubmed
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pubmed-article:11252619pubmed:volume57lld:pubmed
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pubmed-article:11252619pubmed:pagination62-73lld:pubmed
pubmed-article:11252619pubmed:dateRevised2007-11-14lld:pubmed
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pubmed-article:11252619pubmed:year2001lld:pubmed
pubmed-article:11252619pubmed:articleTitleCovariate measurement error adjustment for matched case-control studies.lld:pubmed
pubmed-article:11252619pubmed:affiliationNational Cancer Institute, Biometric Research Branch, DCTD, Bethesda, Maryland 20892-7434, USA. lm5h@nih.govlld:pubmed
pubmed-article:11252619pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:11252619pubmed:publicationTypeResearch Support, U.S. Gov't, P.H.S.lld:pubmed