5 citations · 7 across the 3 of their papers we have counts for
3 papers
Supervised dimensionality reduction for multiple imputation by chained equations
Edoardo Costantini, Kyle M. Lang, Klaas Sijtsma
Multivariate imputation by chained equations (MICE) is one of the most popular approaches to address missing values in a data set. This approach requires specifying a univariate im…
High-dimensional Imputation for the Social Sciences: a Comparison of State-of-the-art Methods
Edoardo Costantini, Kyle M. Lang, Tim Reeskens +1
Including a large number of predictors in the imputation model underlying a multiple imputation (MI) procedure is one of the most challenging tasks imputers face. A variety of high…
Solving the "many variables" problem in MICE with principal component regression
Edoardo Costantini, Kyle M. Lang, Klaas Sijtsma +1
Multiple Imputation (MI) is one of the most popular approaches to addressing missing values in questionnaires and surveys. MI with multivariate imputation by chained equations (MIC…