I have data on ~100 subjects: blood values taken on different days (day 1, 4, 7, and 11). The subjects undergo different treatments (but only one treatment per subject) and may develop different complications and I'd like to see whether these are reflected in the evolution of their blood values.
As the values on different days are not independent, simple linear regression seems wrong. The time sequences are also too short and the time points are not equally spaced, so I cannot use time series analysis. I have no experience with mixed linear models, but I doubt they are applicable on data with 100 groups of 4 (3 if I use differences) observations in each.
So, what are my options?
P.S. The existing answers to analysis of measurements over time, How to compare short (9 points) time-series, and Predicting on data consisting of many independent short time series? don't seem relevant for my question.