Multiple imputation using chained equations: issues and guidance for practice

Statistics in medicine 30(4):377–399, 2011 2010 Ian R. WhitePatrick RoystonAngela M. Wood

Multiple imputation by chained equations (MICE) is a flexible and practical approach to handling missing data. We describe the principles of the method and show how to impute categorical and quantitative variables, including skewed variables... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Multivariate Time Series Imputation Beijing Air Quality MICE MAE (PM2.5) 27.42 # 5
Multivariate Time Series Imputation KDD CUP Challenge 2018 MICE MSE (10% missing) 0.468 # 4
Multivariate Time Series Imputation PhysioNet Challenge 2012 MICE MAE (10% of data as GT) 0.634 # 4
Multivariate Time Series Imputation UCI localization data MICE MAE (10% missing) 0.477 # 4

Methods used in the Paper


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