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Table 3 Details of the five missing data methods investigated

From: Comparison of imputation methods for handling missing covariate data when fitting a Cox proportional hazards model: a resampling study

Label Missing data method
CC Complete case analysis
SI Single imputation using regression switching imputation with predictive mean matching with only one imputation fitted using the 'pmm' function within the mice library [40]
MI-aregImpute MI fitting flexible additive imputation models using the 'aregImpute' function in the Hmisc library [21]
MI-MICE MI using regression switching imputation with linear or logistic regression models as appropriate for each incomplete covariate fitted using the mice library [40]
MI-MICE-PMM MI using regression switching imputation with predictive mean matching fitted using the 'pmm' function within the mice library [40]
  1. Key: PMM = predictive mean matching; MI = multiple imputation