Missing data imputation using K-Nearest Neighbors Classification?
Is it currently possible to use the machine learning features in JASP for the imputation of missing data? I am thinking more specifically about the Classification methods, as my relevant variables are categorical (dichotomous). To add to the complexity, my data are longitudinal with three time points and nested within participants. I have looked into K-Nearest Neighbours Classification, but unfortunately, I do not quite understand whether what I am trying to do is possible.
Thank you for your help in advance.