I am trying to study attrition amongst students during their 3 year bachelor's degree. If I measure values of various features every semester over a 3 year period (or any other frequency), only some features change over time, some don't. The student profile data such as what their Year 12 score was or if they are first in family to attend Uni doesn't change over time. But GPA, the number of units they enroll themselves in etc. changes with time. How can I handle this in Survival Analysis ? How can I account for the fact that the first 3 rows belong to 1 student and the next 2 to another student.
Note: It's more important for me to take into account the impact of changing values of some features on attrition (such as how study load went from 4 to 3 to 2) than to know at what point in their course they quit - which is good to know as well. Holistically considering the change in values of some features if it has resulted in attrition is what I want to know. If I do a binary classification, I am only considering a snapshot in time because I can have only 1 row per student but not the entire student experience.
Student Year GPA Year12-score First-in-family Age Study-Load Attrition S1 Y1 4.5 78% Yes 20 4 No S1 Y2 6.2 78% Yes 21 3 No S1 Y3 6.1 78% Yes 22 2 Yes S2 Y1 8.2 82% No 19 2 No S2 Y2 6.9 82% No 20 2 Yes
Also, given the fact that Student S1 attrited in Year 3, should I mark the Attrition Label as "Yes" for all 3 years ?