American Journal of Epidemiology Vol. 136, No. 11: 1400-1413
Copyright © 1992 by The Johns Hopkins University School of Hygiene and Public Health
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Correction of Logistic Regression Relative Risk Estimates and Confidence Intervals for Random Within-Person Measurement Error
1Channing Laboratory, Department of Medicine, Harvard Medical School, and Department of Medicine, Brigham and Women's Hospital Boston, MA
2Department of Biostatistics, Harvard School of Public Health Boston, MA.
3Departments of Epidemiology and Biostatistics, Harvard School of Public Health Boston, MA.
4Departments of Epidemiology and Nutrition, Harvard School of Public Health Boston, MA.
Reprint requests to Dr B. Rosner, Channing Laboratory, Harvard Medical School, 180 Longwood Avenue, Boston, MA 02115.
Frequently, covariates used in a logistic regression are measured with error. The authors previously described the correction of logistic regression relative risk estimates for measurement error in one or more covariates when a "gold standard" is available for exposure assessment. For some exposures (e.g., serum cholesterol), no gold standard exists, and one must assess measurement error via a reproducibiiity substudy. In this paper, the authors present measurement error methods for logistic regression when there is error (possibly correlated) in one or more covariates and one has data from both a main study and a reproducibiiity substudy. Confidence intervals from this procedure reflect error in parameter estimates from both studies. These methods are applied to the Framingham Heart Study, where the 10year incidence of coronary heart disease is related to several coronary risk factors among 1, 731 men disease-free at examination 4. Reproducibiiity data are obtained from the subgroup of 1, 346 men seen at examinations 2 and 3. Estimated odds ratios comparing extreme quintiles for risk factors with substantial error were increased after correction for measurement error (serum cholesterol, 2.2 vs. 2.9; serum glucose, 1.3 vs. 1.5; systolic blood pressure, 2.8 vs. 3.8), but were generally decreased or unchanged for risk factors with little or no error (body mass index, 1.6 vs. 1.6; age 6569 years vs. 3544 years, 4.3 vs. 3.8; smoking, 1.7 vs. 1.7). Am J Epidemiol 1992; 136: 140013.
biometry; epidemiologic methods; reliability
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