I am working with a dataset which consists of both categorical (14 vars) and continuous variables (5). Each categorical variable consists of a minimum of 2 categories up to 106 categories.

The aim of my study is to find those variables that are mostly important for my analysis, I was thinking of using Principal Component Analysis (PCA) how ever from my understanding this can only be used for continuous variables.

Anyone can help me what I can use for dimension reduction, I will be using R-studio to carry out analysis.



Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.