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Zero‐cell corrections in random‐effects meta‐analyses
Author(s) -
Weber Frank,
Knapp Guido,
Ickstadt Katja,
Kundt Günther,
Glass Änne
Publication year - 2020
Publication title -
research synthesis methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.376
H-Index - 35
eISSN - 1759-2887
pISSN - 1759-2879
DOI - 10.1002/jrsm.1460
Subject(s) - zero (linguistics) , estimator , statistics , odds , standard error , mathematics , continuity correction , random effects model , meta analysis , algorithm , computer science , logistic regression , medicine , negative binomial distribution , philosophy , linguistics , beta binomial distribution , poisson distribution
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 1 2 to all cells of all the individual studies' 2 × 2 tables independently of any zero‐cell occurrences and (b) adding 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).