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Avoiding pitfalls when combining multiple imputation and propensity scores
Overcoming bias due to confounding and missing data is challenging when analyzing observational data. Propensity scores are commonly used to account for the first problem and multiple imputation for the latter. Unfortunately, it is not known how best to proceed when both techniques are required. We...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
John Wiley and Sons Inc.
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856837/ https://www.ncbi.nlm.nih.gov/pubmed/31512265 http://dx.doi.org/10.1002/sim.8355 |