The concept of residual confounding in regression models and some applications
Abstract
In this paper the concept of residual confounding is generalized to various types of regression models such as logistic regression or Cox regression. Residual confounding and a newly suggested parameter, the relative residual confounding, are defined on the regression parameters of the models. The estimator gives the proportion of confounding which has been removed by incomplete adjustment. The concept quantifies the effects of categorizing continuous covariables and of model misspecification. These are investigated by a simulation study and with data from an epidemiological investigation. A case‐control study of laryngeal cancer is used to illustrate the residual confounding effect of arbitrary transformation of a continuous confounder, smoking, on the effect of alcohol consumption on laryngeal cancer risk. The data also showed that categorization into two levels can yield high residual confounding. The parameters described in this paper are of some use in quantifying the effect of inadequate adjustment for confounding variables.
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Error in measurement of potential confounders can increase the risk of residual confounding.
“Error in measurement of potential confounders can increase the risk of residual confounding [ 62 , 63 ].”
From Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration (2007) · cites this paper as [62]
If a continuous confounder is grouped, residual confounding may occur, whereby some of the variable's confounding effect remains unadjusted for.
“If a continuous confounder is grouped, residual confounding may occur, whereby some of the variable's confounding effect remains unadjusted for (see Box 5 ) [ 62 , 89 ].”
From Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration (2007) · cites this paper as [62]
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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
“If a continuous confounder is grouped, residual confounding may occur, whereby some of the variable’s confounding effect remains unadjusted for (see Box 5) [62,89].”
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- Authors
- Becher, H.
- Affiliations
- German Cancer Research Center (DE)
- Corresponding author
- Becher, Heiko
- ORCID
- Becher, Heiko
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 1992-01
- Volume
- 11
- Issue
- 13
- Pages
- 1747-1758
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W2140816967
- Cited by
- 168
- References
- 2
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 7 · 2023: 15 · 2022: 9 · 2021: 11 · 2020: 6 · 2019: 7 · 2018: 4 · 2017: 6 · 2016: 7 · 2015: 6 · 2014: 4 · 2013: 5 · 2012: 5
- FWCI
- 1.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Statistics in Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Keywords
- residual confounding, confounding adjustment, model misspecification, logistic regression, Cox proportional hazards model, smoking, alcohol consumption, laryngeal cancer, case-control study
- MeSH terms
- Alcohol Drinking, Humans, Laryngeal Neoplasms, Regression Analysis, Risk Factors, Smoking, Bias, Confounding Factors, Epidemiologic, Logistic Models
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