Literature DB >> 8793367

Correcting for exposure misclassification using an alloyed gold standard.

H Brenner1.   

Abstract

Validation studies are increasingly employed to estimate and correct for exposure misclassification in epidemiologic studies. Often, however, the reference procedure used for validation is less than perfect. This phenomenon may lead to biased estimates of misclassification rates and hence of "corrected" measures of associations. In particular, it has been demonstrated that basic matrix correction procedures to correct for presumably nondifferential exposure misclassification may yield strongly misleading results in the case of an imperfect gold standard. The problem arises because apparent misclassification (misclassification with respect to an alloyed gold standard) is often differential even if true misclassification (misclassification with respect to true exposure status) is nondifferential. Therefore, correction procedures for differential rather than nondifferential misclassification should be employed in the presence of an alloyed gold standard.

Mesh:

Year:  1996        PMID: 8793367     DOI: 10.1097/00001648-199607000-00011

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


  14 in total

Review 1.  Measurement, analysis and interpretation of examiner reliability in caries experience surveys: some methodological thoughts.

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Journal:  Clin Oral Investig       Date:  2010-10-13       Impact factor: 3.573

2.  Reducing bias from test misclassification in burden of disease studies: use of test to actual positive ratio--new test parameter.

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Journal:  Croat Med J       Date:  2008-06       Impact factor: 1.351

3.  Extended Matrix and Inverse Matrix Methods Utilizing Internal Validation Data When Both Disease and Exposure Status Are Misclassified.

Authors:  Li Tang; Robert H Lyles; Ye Ye; Yungtai Lo; Caroline C King
Journal:  Epidemiol Methods       Date:  2013-09-01

4.  Validation data-based adjustments for outcome misclassification in logistic regression: an illustration.

Authors:  Robert H Lyles; Li Tang; Hillary M Superak; Caroline C King; David D Celentano; Yungtai Lo; Jack D Sobel
Journal:  Epidemiology       Date:  2011-07       Impact factor: 4.822

5.  Sleep apnea and pesticide exposure in a study of US farmers.

Authors:  Brittney O Baumert; Megan Ulmer Carnes; Jane A Hoppin; Chandra L Jackson; Dale P Sandler; Laura Beane Freeman; Paul K Henneberger; David M Umbach; Srishti Shrestha; Stuart Long; Stephanie J London
Journal:  Sleep Health       Date:  2017-09-28

6.  Transient elastography for the noninvasive assessment of liver fibrosis: a multicentre Canadian study.

Authors:  Robert P Myers; Magdy Elkashab; Mang Ma; Pam Crotty; Gilles Pomier-Layrargues
Journal:  Can J Gastroenterol       Date:  2010-11       Impact factor: 3.522

7.  Comparison between the abuse assessment screen and the revised conflict tactics scales for measuring physical violence during pregnancy.

Authors:  M E Reichenheim; C L Moraes
Journal:  J Epidemiol Community Health       Date:  2004-06       Impact factor: 3.710

8.  Sensitivity analysis for nonignorable missingness and outcome misclassification from proxy reports.

Authors:  Michelle Shardell; Eleanor M Simonsick; Gregory E Hicks; Barbara Resnick; Luigi Ferrucci; Jay Magaziner
Journal:  Epidemiology       Date:  2013-03       Impact factor: 4.822

9.  Effects of exposure measurement error in the analysis of health effects from traffic-related air pollution.

Authors:  Lisa K Baxter; Rosalind J Wright; Christopher J Paciorek; Francine Laden; Helen H Suh; Jonathan I Levy
Journal:  J Expo Sci Environ Epidemiol       Date:  2009-02-18       Impact factor: 5.563

10.  Evaluation of the Webler-Brown model for estimating tetrachloroethylene exposure from vinyl-lined asbestos-cement pipes.

Authors:  Lisa A Spence; Ann Aschengrau; Lisa E Gallagher; Thomas F Webster; Timothy C Heeren; David M Ozonoff
Journal:  Environ Health       Date:  2008-06-02       Impact factor: 5.984

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