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Regularized approach for data missing not at random
It is common in longitudinal studies that missing data occur due to subjects’ no response, missed visits, dropout, death or other reasons during the course of study. To perform valid analysis in this setting, data missing not at random (MNAR) have to be considered. However, models for data MNAR ofte...
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| Veröffentlicht in: | Stat Methods Med Res |
|---|---|
| Hauptverfasser: | , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2017
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7162734/ https://ncbi.nlm.nih.gov/pubmed/28671033 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1177/0962280217717760 |
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