Multiple imputation for continuous variables using a Bayesian principal component analysis
Multiple imputation for continuous variables using a Bayesian principal component analysis
We propose a multiple imputation method based on principal component analysis (PCA) to deal with incomplete continuous data. To reflect the uncertainty of the parameters from one imputation to the next, we use a Bayesian treatment of the PCA model. Using a simulation study and real data sets, the method …