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What impact do assumptions about missing data have on conclusions? A practical sensitivity analysis for a cancer survival registry
BACKGROUND: Within epidemiological and clinical research, missing data are a common issue and often over looked in publications. When the issue of missing observations is addressed it is usually assumed that the missing data are ‘missing at random’ (MAR). This assumption should be checked for plausi...
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| 出版年: | BMC Med Res Methodol |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2017
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| 主題: | |
| オンライン・アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5294884/ https://ncbi.nlm.nih.gov/pubmed/28166735 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12874-017-0301-0 |
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