Exposure-measurement error is frequently ignored when interpreting epidemiologic study results

Anne M. Jurek, George Maldonado, Sander Greenland, Timothy R. Church

Research output: Contribution to journalArticlepeer-review

71 Scopus citations

Abstract

Introduction: One important source of error in study results is error in measuring exposures. When interpreting study results, one should consider the impact that exposure-measurement error (EME) might have had on study results. Methods: To assess how often this consideration is made and the form it takes, journal articles were randomly sampled from original articles appearing in the American Journal of Epidemiology and Epidemiology in 2001, and the International Journal of Epidemiology between December 2000 and October 2001. Results: Twenty-two (39%) of the 57 articles surveyed mentioned nothing about EME. Of the 35 articles that mentioned something about EME, 16 articles described qualitatively the effect EME could have had on study results. Only one study quantified the impact of EME on study results; the investigators used a sensitivity analysis. Few authors discussed the measurement error in their study in any detail. Conclusions: Overall, the potential impact of EME on error in epidemiologic study results appears to be ignored frequently in practice.

Original languageEnglish (US)
Pages (from-to)871-876
Number of pages6
JournalEuropean Journal of Epidemiology
Volume21
Issue number12
DOIs
StatePublished - Dec 2006

Bibliographical note

Funding Information:
Disclaimer: Although the research described in the article has been funded in part by the U.S. Environmental Protection Agency’s STAR program through grant (U-91615801-0), it has not been subject to any EPA review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred.

Funding Information:
This research has been supported by a grant from the U.S. Environmental Protection Agency’s Science to Achieve Results (STAR) program.

Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.

Keywords

  • Bias
  • Epidemiologic methods
  • Measurement error

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