I'm studying data on a project that measures 12 variables each month to a group of people, with the outcome variable being a continuous scale score. As there are several variables involved, between categorical and continuous, I would like to be able to perform a dimensionality reduction, after performing a regression, and thus evaluate the relationship of the outcome with those variables.
I was thinking that a good strategy would be to perform a PCA, but since it involves repeated measurements at certain times, then I would like to know if it can be done. Is there a method that is more appropriate to explore the data that I have?
Previously I saw this question, which is a little closer to my question, but I didn't find that there was an answer. But if you wanted to know if the MFA can also be a good approximation. Thank you!
