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A comparison of different methods to handle missing data in the context of propensity score analysis
Propensity score analysis is a popular method to control for confounding in observational studies. A challenge in propensity methods is missing values in confounders. Several strategies for handling missing values exist, but guidance in choosing the best method is needed. In this simulation study, w...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Netherlands
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6325992/ https://www.ncbi.nlm.nih.gov/pubmed/30341708 http://dx.doi.org/10.1007/s10654-018-0447-z |