When and how should multiple imputation be used for handling missing data in randomised clinical trials – a practical guide with flowcharts
Janus Christian Jakobsen, Christian Gluud, Jørn Wetterslev et al. · 2017
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Description
Janus Jakobsen, Christian Gluud, Jorn Wetterslev, and coauthors wrote this practical guide in 2017. It covers missing data in randomized clinical trials, a problem that can bend results if handled badly. How much bias appears depends on why the data went missing.
The guide explains when filling in missing values by multiple imputation is a sound choice. Flowcharts walk readers through checks on the trial design and the pattern of missing values. Worked examples show the steps in real trials. Trial teams can use the guide to plan analyses that reviewers and readers can trust more.
Catalog record
| CREATOR | Janus Christian Jakobsen, Christian Gluud, Jørn Wetterslev et al. |
|---|---|
| YEAR | 2017 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 52 KB |
| LICENSE | Creative Commons Attribution License |
| RIGHTS | CC BY |
| SOURCE | PubMed Central |