I have a dataset where each record is a purchase, with user, datetime, low-cost/high-cost option chosen (y, boolean), quality, and opportunity price (the lowest priced option) as variables. The goal is to predict whether someone will purchase a low-cost option or a high cost option.
However, some users have multiple records because they have made multiple purchases at different times (I don't care about time in this case).
What is a good model / approach for this sort of data? I am assuming I cant just leave the records in their as is for a standard Logistic Regression because it would break the assumption of iid.