Zero-cell corrections in random-effects meta-analyses

Abstract

The standard estimator for the log odds ratio (the unconditional maximum likelihood estimator) and the delta-method estimator for its standard error are not defined if the corresponding 2 × 2 table contains at least one "zero cell". This is also an issue when estimating the overall log odds ratio in a meta-analysis. It is well known that correcting for zero cells by adding a small increment should be avoided. Nevertheless, these zero-cell corrections continue to be used. With this Brief Method Note, we want to warn of a particularly bad zero-cell correction. For this, we conduct a simulation study comparing the following two zero-cell corrections under the ordinary random-effects model: (a) adding $\frac{1}{2}$ to all cells of all the individual studies' 2 × 2 tables independently of any zero-cell occurrences and (b) adding $\frac{1}{2}$ to all cells of only those 2 × 2 tables containing at least one zero cell. The main finding is that correction (a) performs worse than correction (b). Thus, we strongly discourage the use of correction (a).

Keywords: binary; continuity correction; meta-analysis; random effects; zero-cell correction.