RESEARCH ARTICLE Comparison of robustness r

a logistic regression. When the outcome prevalence is high (>10%), the OR can still be estimated by using the logistic regression model, but the OR is no longer an ac-ceptable estimate for RR [1]. Interpreting the OR as be-ing equivalent to the RR still occurs in medical research, leading to overstated effect in the study findings [2,3]. leads to higher degree of exaggeration. Zhang and Yu proposed a formula to convert the adjusted OR derived from the logistic regression model to a risk ratio in studies with common outcomes [4]. However, the method was noted by McNutt et al. to produce biases in both point es-timates and confidence intervals (CIs) [5]. Miettinen sug-gested the doubling-of-cases method to estimate OR as an approximation of RR using logistic regression based on a modified dataset [6]. Schouten et al. improved the method by applying robust standard errors [7]. However, this method was mentioned by Skov et al. to produce preva-lence greater than one [8]. Several model-based method