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stat.ME2021
Clustering with missing data: which imputation model for which cluster analysis method?
Vincent Audigier, Ndèye Niang, Matthieu Resche-Rigon
Multiple imputation (MI) is a popular method for dealing with missing values. One main advantage of MI is to separate the imputation phase and the analysis one. However, both are r…
stat.ME2015★ 1 cited
MIMCA: Multiple imputation for categorical variables with multiple correspondence analysis
Vincent Audigier, François Husson, Julie Josse
We propose a multiple imputation method to deal with incomplete categorical data. This method imputes the missing entries using the principal components method dedicated to categor…