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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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| Wydane w: | Stat Med |
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| 1. autor: | |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
2019
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| Hasła przedmiotowe: | |
| Dostęp online: | 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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