Factor analysis after multuple imputation


I am trying to run an EFA on 20 variables, but have some missing observations. My dataset contains both continuous and categorical variables. So, I am using the package FactoMineR with the function FAMD to run the EFA. In handling missing data, I want to use multiple imputation. I ran the following:

Creates 50 multiply imputed datasets

res.mi <- MIFAMD(foodset1, ncp = 5, nboot=50)

Get an object with all 50 datasets

imp.mice <- prelim(res.mifamd, dataset1)

So, now how do I use this imp.mice object to tell R to run FAMD on all 50 datasets and give me a pooled result of the eigen values, variance and cumulative variance from the factor analysis?
I have tried the below, which ofc doesn't work:
fit <- with(data = imp.mice, FAMD(dataset1, ncp = 5))


This topic was automatically closed 21 days after the last reply. New replies are no longer allowed.