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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, 2020. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 23 October 2020

Response rates and their maximization

Response rates and their maximization

Chapter:
(p.357) 11 Response rates and their maximization
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/9780198509851.003.0011

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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