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Maximum likelihood estimation with missing outcomes: From simplicity to complexity
Many clinical or prevention studies involve missing or censored outcomes. Maximum likelihood (ML) methods provide a conceptually straightforward approach to estimation when the outcome is partially missing. Methods of implementing ML methods range from the simple to the complex, depending on the typ...
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| Gepubliceerd in: | Stat Med |
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| Hoofdauteur: | |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
2019
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6879193/ https://ncbi.nlm.nih.gov/pubmed/31392751 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.8319 |
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