The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Estimating the Relative Risk in Cohort Studies and Clinical Trials of Common Outcomes
Abstract
Logistic regression yields an adjusted odds ratio that approximates the adjusted relative risk when disease incidence is rare (<10%), while adjusting for potential confounders. For more common outcomes, the odds ratio always overstates the relative risk, sometimes dramatically. The purpose of this paper is to discuss the incorrect application of a proposed method to estimate an adjusted relative risk from an adjusted odds ratio, which has quickly gained popularity in medical and public health research, and to describe alternative statistical methods for estimating an adjusted relative risk when the outcome is common. Hypothetical data are used to illustrate statistical methods with readily accessible computer software.
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Cited by
Wang, X., Ouyang, Y., Liu, J., Zhu, M., Zhao, G., Bao, W., & Hu, F. B. (2014) · BMJ · doi:10.1136/bmj.g4490 · Cited by 1,596
Ronksley, P. E., Brien, S. E., Turner, B. J., Mukamal, K. J., & Ghali, W. A. (2011) · BMJ · doi:10.1136/bmj.d671 · Cited by 1,610
Active Smoking and the Risk of Type 2 Diabetes: A Systematic Review and Meta-analysis
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Mechanical ventilation guided by esophageal pressure in acute lung injury.
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Suurmond, R., van Rhee, H., & Hak, T. (2017) · Research Synthesis Methods · doi:10.1002/jrsm.1260 · Cited by 881
Metadata
- Authors
- McNutt, L.-A.
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2003-05-15
- Volume
- 157
- Issue
- 10
- Pages
- 940-943
- ISSN
- 0002-9262 (ISSN-L)
- OpenAlex
- W2153941399
- Cited by
- 2,096
- References
- 13
- FWCI
- 25.75
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
