result_mice is a function that retrieve the final imputed dataset after running function mice in the 'mice' package. As for categorical columns, both factor form and onehot probability vector form are returned

More details about the MICE implementation could be found in the documentation of function mice from the 'mice' package.

result_mice(res, impnum, col_cat = c())

Arguments

res

Result returned by mice function

impnum

Number of multiple imputations

col_cat

Categorical columns index

Value

ximp Final imputed data matrix, which is obtained with Rubin's Rule. ximp.disj Final imputed data matrix of same type as 'ximp' for the numeric columns. For the categorical columns, the prediction of probability for each category is shown in form of onehot probability vector.

References

Van Buuren, S., Groothuis-Oudshoorn, K. (2011). mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software, 45(3), 1-67. https://www.jstatsoft.org/v45/i03/

Van Buuren, S. (2018). Flexible Imputation of Missing Data. Second Edition. Chapman & Hall/CRC. Boca Raton, FL.

Van Buuren, S., Brand, J.P.L., Groothuis-Oudshoorn C.G.M., Rubin, D.B. (2006) Fully conditional specification in multivariate imputation. Journal of Statistical Computation and Simulation, 76, 12, 1049--1064.

Van Buuren, S. (2007) Multiple imputation of discrete and continuous data by fully conditional specification. Statistical Methods in Medical Research, 16, 3, 219--242.

Van Buuren, S., Boshuizen, H.C., Knook, D.L. (1999) Multiple imputation of missing blood pressure covariates in survival analysis. Statistics in Medicine, 18, 681--694.

Brand, J.P.L. (1999) Development, implementation and evaluation of multiple imputation strategies for the statistical analysis of incomplete data sets. Dissertation. Rotterdam: Erasmus University.

Statistical Analysis with Missing Data, by Little and Rubin, 2002