I've recently conducted a k-prototypes R routine on some mixed data.
In particular, the data is health data concerning a certain public health intervention, with categorical variables for health scores and numerical demographic data such as age
The utility scores were measured at different points in time, with one sample at week 1, and one sample at week 10.
At the moment, I have only conducted clustering analysis on one of these samples. However, I wondered if there is a recognised routine for making inference on the clusters between week 1, and week 10.
All feedback would be appreciated. I recognise that it is not quite longitudinal clustering, but more comparing two different clustering states.