Handling missing values with/in multivariate data analysis (principal component methods)

Description

Imputation of incomplete continuous or categorical datasets; Missing values are imputed with a principal component analysis (PCA), a multiple correspondence analysis (MCA) model or a multiple factor analysis (MFA) model; Perform multiple imputation with and in PCA

Details

Author(s)

Francois Husson, Julie Josse

Maintainer: husson@agrocampus-ouest.fr

References

Josse, J. & Husson, F. (2012). Handling missing values in exploratory multivariate data analysis methods. Journal de la SFdS, 153(2), pp. 79-99.

Julie Josse, Francois Husson (2016). missMDA: A Package for Handling Missing Values in Multivariate Data Analysis. Journal of Statistical Software, 70(1), 1-31. doi:10.18637/jss.v070.i01

Some videos: https://www.youtube.com/playlist?list=PLnZgp6epRBbQzxFnQrcxg09kRt-PA66T_

Results