Factors associated with: problems of using exploratory multivariable regression to identify causal risk factors

Lewer and colleagues explain why risk factors for a health outcome should not be studied by putting several candidate independent variables (exposures) into a multivariable regression model and identifying which are statistically significant after mutual adjustment.

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Publication Details

Journal
BMJ Medicine
Published
2025-10-01
DOI
https://doi.org/10.1136/bmjmed-2025-001375
Citations
2
Primary Topic
Statistical Methods in Epidemiology
Type
article
Field-Weighted Citation Impact
5.26
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article

Factors associated with: problems of using exploratory multivariable regression to identify causal risk factors

Thomas D. Brothers, Elizabeth O’Nions, John Pickavance, Dan Lewer
2 citations
BMJ Medicine
Statistical Methods in Epidemiology
5.26
article

Factors associated with: problems of using exploratory multivariable regression to identify causal risk factors

Thomas D. Brothers, Elizabeth O’Nions, John Pickavance, Dan Lewer
article en
2 citations

Abstract

Lewer and colleagues explain why risk factors for a health outcome should not be studied by putting several candidate independent variables (exposures) into a multivariable regression model and identifying which are statistically significant after mutual adjustment.

BMJ MedicineVol. 4(1)
Dalhousie University (CA), University of Bradford (GB), University College London (GB)
Openalex Percentile: Top 4%
Statistical Methods in Epidemiology
5.26
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