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.
Keywords
Relative riskOdds ratioConfoundingMedicineLogistic regressionOddsDiagnostic odds ratioStatisticsIncidence (geometry)Cohort studyConfidence intervalDemographyMathematicsInternal medicine
MeSH Terms
Clinical Trials as TopicCohort StudiesCross-Sectional StudiesData InterpretationStatisticalHealth Services ResearchHumansOdds RatioOutcome AssessmentHealth CarePoisson DistributionRisk
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Publication Info
- Year
- 2003
- Type
- article
- Volume
- 157
- Issue
- 10
- Pages
- 940-943
- Citations
- 2054
- Access
- Closed
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Cite This
Louise‐Anne McNutt
(2003).
Estimating the Relative Risk in Cohort Studies and Clinical Trials of Common Outcomes.
American Journal of Epidemiology
, 157
(10)
, 940-943.
https://doi.org/10.1093/aje/kwg074
Identifiers
- DOI
- 10.1093/aje/kwg074
- PMID
- 12746247