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Zero-cell corrections in random-effects meta-analyses.
Weber, Frank; Knapp, Guido; Ickstadt, Katja; Kundt, Günther; Glass, Änne.
Affiliation
  • Weber F; Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany.
  • Knapp G; Faculty of Statistics, TU Dortmund University, Dortmund, Germany.
  • Ickstadt K; Faculty of Statistics, TU Dortmund University, Dortmund, Germany.
  • Kundt G; Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany.
  • Glass Ä; Institute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany.
Res Synth Methods ; 11(6): 913-919, 2020 Nov.
Article in En | MEDLINE | ID: mdl-32991790
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).
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Meta-Analysis as Topic / Statistics as Topic / Data Interpretation, Statistical Type of study: Clinical_trials / Etiology_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Limits: Humans Language: En Journal: Res Synth Methods Year: 2020 Document type: Article Affiliation country: Germany Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Meta-Analysis as Topic / Statistics as Topic / Data Interpretation, Statistical Type of study: Clinical_trials / Etiology_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Limits: Humans Language: En Journal: Res Synth Methods Year: 2020 Document type: Article Affiliation country: Germany Country of publication: United kingdom