Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study
Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The “true” imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can acc...
| Main Authors: | , , , , |
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| Format: | Online |
| Language: | English |
| Published: |
Oxford University Press
2014
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3939843/ |