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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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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 10 May 2021

Response rates and their maximization

Response rates and their maximization

(p.357) 11 Response rates and their maximization
Principles of Exposure Measurement in Epidemiology

Emily White

Bruce K. Armstrong

Rodolfo Saracci

Oxford University Press

The emphasis of this chapter is on response rates and their maximization, and how low response rates may bias the results of epidemiologic studies. Specifically, response bias — a form of selection bias — is caused by non-participation of eligible individuals in a case-control study or by loss to follow-up of participants in a prospective study. Non-response can be due to subject refusal or failure to reach the subject. The chapter defines response rates, examines factors associated with non-response, and describes the adverse effects of non-response. The response rate (the number of study participants/estimated eligible individuals on the sampling frame) should be carefully estimated and always reported. Techniques to improve initial response to participate in a study, to maintain participants in longitudinal studies, and to locate lost participants are discussed.

Keywords:   response rate, cooperation rate, completion rate, response bias, selection bias, non-response, loss to follow-up, incentives, tracing subjects, run-in period

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