Mavridis, D;
White, IR;
(2019)
Dealing with missing outcome data in meta-analysis.
Research Synthesis Methods
10.1002/jrsm.1349.
(In press).
Preview |
Text
White_Mavridis_et_al-2019-Research_Synthesis_Methods.pdf - Published Version Download (1MB) | Preview |
Abstract
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 re-weight 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 minimise the problem of missing outcome data in meta-analysis.
| Type: | Article |
|---|---|
| Title: | Dealing with missing outcome data in meta-analysis |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/jrsm.1349 |
| Publisher version: | https://doi.org/10.1002/jrsm.1349 |
| Language: | English |
| Additional information: | Copyright © 2019 The Authors Research Synthesis Methods Published by John Wiley & Sons LtdThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | informative missingness odds ratio, informative missingness parameter, meta-analysis, missing data, missing not at random |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10075044 |
Archive Staff Only
 |
View Item |
