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Principles of Exposure Measurement in EpidemiologyCollecting, Evaluating, and Improving Measures of Disease Risk Factors$
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Emily White, Bruce K. Armstrong, and Rodolfo Saracci

Print publication date: 2008

Print ISBN-13: 9780198509851

Published to Oxford Scholarship Online: September 2009

DOI: 10.1093/acprof:oso/9780198509851.001.0001

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Reducing measurement error and its effects

Reducing measurement error and its effects

Chapter:
(p.141) 5 Reducing measurement error and its effects
Source:
Principles of Exposure Measurement in Epidemiology
Author(s):

Emily White

Bruce K. Armstrong

Rodolfo Saracci

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198509851.003.0005

The primary goal when measuring exposures (risk factors) in an epidemiological study should be minimizing measurement error. Several approaches to the reduction of measurement error and its effects are discussed in this chapter. First, adjustment procedures are briefly covered; these are methods of ‘correcting’ study results for the effect of measurement error by using information from a validity or reliability study. Next is the use of multiple measures of exposure in an epidemiologic study, to create an average, score or index for each subject. Finally minimization of error by way of quality control procedures is discussed. These procedures include careful design of the data collection forms, complete documentation of study procedures, pre-testing of the data collection instrument(s), appropriate training and supervision of data collectors, and documentation of raw, corrected and computed data variables via codebooks.

Keywords:   de-attenuation, multiple measures, scores, internal consistency reliability, quality control, study procedure manual, editing, coding

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