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Dealing with missing outcome data in meta-analysis
- Type de document
- EXTERNAL_DOCUMENT
- Extension
- png
- Taille
- 285 Ko
- Modifié
- 21/10/22 14:02 par mir mir
- Créé(e)
- 21/10/22 14:02 par mir mir
- Localisation
- PUBLIC
- Notations
-
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Version 1.0Par mir mir, sur 21/10/22 14:02Log Pas de changement
Résumé
Missing data result in less precise and possibly biased effect estimates in single studies. Bias arising from studies with incomplete outcome data is naturally propagated in a meta-analysis. Conventional analysis using only individuals with available data is adequate when the meta-analyst can be confident that the data are missing at random (MAR) in every study—that is, that the probability of missing data does not depend on unobserved variables, conditional on observed variables. Usually, such confidence is unjustified as participants may drop out due to lack of improvement or adverse effects. The MAR assumption cannot be tested, and a sensitivity analysis to assess how robust results are to reasonable deviations from the MAR assumption is important. Two methods may be used based on plausible alternative assumptions about the missing data. Firstly, the distribution of reasons for missing data may be used to impute the missing values. Secondly, the analyst may specify the magnitude and uncertainty of possible departures from the missing at random assumption, and these may be used to correct bias and reweight the studies. This is achieved by employing a pattern mixture model and describing how the outcome in the missing participants is related to the outcome in the completers. Ideally, this relationship is informed using expert opinion. The methods are illustrated in two examples with binary and continuous outcomes. We provide recommendations on what trial investigators and systematic reviewers should do to minimize the problem of missing outcome data in meta-analysis.
Le projet COMPAR-EU a été financé par le programme de recherche et d'innovation Horizon 2020 de l'Union européenne dans le cadre de la convention de subvention n° 754936.
Veuillez noter qu'il s'agit de la version bêta de la plateforme COMPAR-EU. Il comprend désormais les résultats complets concernant le diabète et, au cours de l'été 2022, les résultats concernant l'obésité, la BPCO ainsi que l'insuffisance cardiaque seront complétés. La plateforme sera également étendue et améliorée pendant les mois à venir.