1998/11/18 by Jun Zhang, Kai Yu · 8 citations
Mathematics · Medicine · #Statistical Methods in Epidemiology #Odds ratio #Medicine #Logistic regression #Relative risk #Incidence (geometry) #Confidence interval #Odds #Population #Rate ratio #Cohort study #Statistics #Demography #Internal medicine #Mathematics #Environmental health
paper · doi:10.1001/jama.280.19.1690
openalex publication_date 1998/11/18 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
Logistic regression is used frequently in cohort studies and clinical trials. When the incidence of an outcome of interest is common in the study population (>10%), the adjusted odds ratio derived from the logistic regression can no longer approximate the risk ratio. The more frequent the outcome, the more the odds ratio overestimates the risk ratio when it is more than 1 or underestimates it when it is less than 1. We propose a simple method to approximate a risk ratio from the adjusted odds ratio and derive an estimate of an association or treatment effect that better represents the true relative risk.