Stat Med. 2005 Jun 15;24(11):1657-82. doi: 10.1002/sim.2055.

Correlated errors in biased surrogates: study designs and methods for measurement error correction.

Statistics in medicine

D Spiegelman, B Zhao, J Kim

PMID: 15736283 DOI: 10.1002/sim.2055

Abstract

A measurement error model proposed previously allows for correlations between subject-specific biases and between random within-subject errors in the surrogates obtained from two modes of measurement. However, most of these model parameters are not identifiable from the standard validation study design, including, importantly, the attenuation factor needed to correct for bias in relative risk estimates due to measurement error. We propose validation study designs that permit estimation and inference for the attenuation factor and other parameters of interest when these correlations are present. We use an estimating equations framework to develop semi-parametric estimators for these parameters, exploiting instrumental variables techniques. The methods are illustrated through application to data from the Nurses' Health Study and Health Professionals' Follow-up Study, and comparisons are made to more restrictive models.

Copyright 2005 John Wiley & Sons, Ltd

MeSH terms

• Bias*
• Chronic Disease / epidemiology
• Cohort Studies
• Computer Simulation
• Diet
• Female
• Humans
• Male
• Models, Statistical*
• Prospective Studies
• Research Design*
• Surveys and Questionnaires

Publication Types

• Journal Article
• Research Support, N.I.H., Extramural
• Research Support, U.S. Gov't, P.H.S.

Grant support

• CA 50597/CA/NCI NIH HHS/United States