Revisiting Bias in Odds Ratios

Abstract

Abstract Ratio measures of effect, such as the odds ratio (OR), are consistent, but the presumption of their unbiasedness is founded on a false premise: The equality of the expected value of a ratio and the ratio of expected values. We show that the invalidity of this assumptions is an important source of empirical bias in ratio measures of effect, which is due to properties of the expectation of ratios of count random variables. We investigate ORs (unconfounded, no effect modification), proposing a correction that leads to “almost unbiased” estimates. We also explore ORs with covariates. We find substantial bias in OR estimates for smaller sample sizes, which can be corrected by the proposed method. Bias correction is more elusive for adjusted analyses. The notion of unbiasedness of OR for the effect of interest for smaller sample sizes is challenged.

Locations

• medRxiv (Cold Spring Harbor Laboratory) - View - PDF