THE EFFECT OF MISCLASSIFICATION IN THE PRESENCE OF COVARIATES
Abstract
The effects of misclassification on analyses involving a discrete covariate are examined. The following points are illustrated: 1) Analogous to the 2 X 2 table case, unbiased misclassification of the study exposure leads to reduction in the observed strength of the association of exposure with disease. 2) Both biased and unbiased misclassification will tend to distort the degree of heterogeneity in the measure of association being considered. 3) Misclassification of a confounder leads to a partial loss of ability to control confounding.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
When correlated risk factors are measured with different degrees of imprecision, the adjusted relative risk associated with them can be biased towards or away from unity.
“However, when correlated risk factors are measured with different degrees of imprecision, the adjusted relative risk associated with them can be biased towards or away from unity [ 204 – 206 ].”
From Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration (2007) · cites this paper as [206]
Cites
Statistical Aspects of the Analysis of Data From Retrospective Studies of Disease
(1959) · JNCI: Journal of the National Cancer Institute · doi:10.1093/jnci/22.4.719 · Cited by 14,689 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Vandenbroucke, J. P., von Elm, E., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., Egger, M., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040297 · Cited by 8,613 · see citing works
Vandenbroucke, J. P., Elm, E. V., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., Egger, M., & initiative, F. T. S. (2007) · Annals of Internal Medicine · doi:10.7326/0003-4819-147-8-200710160-00010-w1 · Cited by 3,543 · see citing works
Vandenbroucke, J. P., von Elm, E., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., & Egger, M. (2014) · International Journal of Surgery · doi:10.1016/j.ijsu.2014.07.014 · Cited by 2,969 · see citing works
Evaluating non-randomised intervention studies
Deeks, J., Dinnes, J., D'Amico, R., Sowden, A., Sakarovitch, C., Song, F., Petticrew, M., & Altman, D. (2003) · Health Technology Assessment · doi:10.3310/hta7270 · Cited by 2,907 · see citing works
Vandenbroucke, J. P., von Elm, E., Altman, D. G., Gøtzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., & Egger, M. (2007) · Epidemiology · doi:10.1097/ede.0b013e3181577511 · Cited by 2,779 · see citing works
Schneeweiss, S., Rassen, J. A., Glynn, R. J., Avorn, J., Mogun, H., & Brookhart, M. A. (2009) · Epidemiology · doi:10.1097/ede.0b013e3181a663cc · Cited by 1,128 · see citing works
Delgado-Rodríguez, M., & Llorca, J. (2004) · Journal of Epidemiology and Community Health · doi:10.1136/jech.2003.008466 · Cited by 1,064 · see citing works
The Impact of Residual and Unmeasured Confounding in Epidemiologic Studies: A Simulation Study
Fewell, Z., Davey Smith, G., & Sterne, J. A. C. (2007) · American Journal of Epidemiology · doi:10.1093/aje/kwm165 · Cited by 734 · see citing works
Trans Fatty Acids and Coronary Heart Disease
Ascherio, A., Katan, M. B., Zock, P. L., Stampfer, M. J., & Willett, W. C. (1999) · New England Journal of Medicine · doi:10.1056/nejm199906243402511 · Cited by 569 · see citing works
Rai, D., Lee, B. K., Dalman, C., Golding, J., Lewis, G., & Magnusson, C. (2013) · BMJ · doi:10.1136/bmj.f2059 · Cited by 365 · see citing works
Assessment and Control for Confounding by Indication in Observational Studies
Psaty, B. M., Koepsell, T. D., Lin, D., Weiss, N. S., Siscovick, D. S., Rosendaal, F. R., Pahor, M., & Furberg, C. D. (1999) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.1999.tb01603.x · Cited by 363 · see citing works
Phillips, A. N., & Smith, G. D. (1991) · Journal of Clinical Epidemiology · doi:10.1016/0895-4356(91)90155-3 · Cited by 275 · see citing works
Interactions in epidemiology: relevance, identification, and estimation
Greenland, S. (2009) · Epidemiology · doi:10.1097/ede.0b013e318193e7b5 · Cited by 204 · see citing works
Self-citationReflection on modern methods: five myths about measurement error in epidemiological research
van Smeden, M., Lash, T. L., & Groenwold, R. H. H. (2020) · International Journal of Epidemiology · doi:10.1093/ije/dyz251 · Cited by 173 · see citing works
David, H. S. (1994) · Ophthalmic Epidemiology · doi:10.3109/09286589409052366 · Cited by 81 · see citing works
Intake of antioxidant nutrients and the risk of skin cancer
Heinen, M. M., Hughes, M. C., Ibiebele, T. I., Marks, G. C., Green, A. C., & van der Pols, J. C. (2007) · European Journal of Cancer · doi:10.1016/j.ejca.2007.09.005 · Cited by 68 · see citing works
Considerations related to vaping as a possible gateway into cigarette smoking: An analytical review
Lee, P. N., Coombs, K. J., & Afolalu, E. F. (2018) · F1000Research · doi:10.12688/f1000research.16928.1 · Cited by 14 · see citing works
- Authors
- GREENLAND, S.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- GREENLAND, SANDER
- ORCID
- GREENLAND, SANDER
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 1980-10
- Volume
- 112
- Issue
- 4
- Pages
- 564-569
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- OpenAlex
- W2260689400
- Cited by
- 494
- References
- 1
- Citations by year
- 2026: 7 · 2025: 13 · 2024: 15 · 2023: 10 · 2022: 14 · 2021: 18 · 2020: 11 · 2019: 13 · 2018: 19 · 2017: 14 · 2016: 10 · 2015: 11 · 2014: 19 · 2013: 18 · 2012: 21
- FWCI
- 2.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- misclassification, discrete covariates, confounding, exposure misclassification, associative strength, measurement error
- MeSH terms
- Biometry, Classification, Epidemiologic Methods, Humans
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review