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Missing data and prediction: the pattern submodel
Missing data are a common problem for both the construction and implementation of a prediction algorithm. Pattern submodels (PS)—a set of submodels for every missing data pattern that are fit using only data from that pattern—are a computationally efficient remedy for handling missing data at both s...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Oxford University Press
2018
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7868046/ https://www.ncbi.nlm.nih.gov/pubmed/30203058 http://dx.doi.org/10.1093/biostatistics/kxy040 |