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Accounting for Informatively Missing Data in Logistic Regression by Means of Reassessment Sampling
We explore the “reassessment” design in a logistic regression setting, where a second wave of sampling is applied to recover a portion of the missing data on a binary exposure and/or outcome variable. We construct a joint likelihood function based on the original model of interest and a model for th...
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| Yayımlandı: | Stat Med |
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| Asıl Yazarlar: | , |
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
2015
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| Konular: | |
| Online Erişim: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4469083/ https://ncbi.nlm.nih.gov/pubmed/25707010 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.6456 |
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