I am using the
mice package to impute some missing values, and it works nicely.
I am facing a tricky strategic question though.
Basically, I am working on predictors of myocardial infarction (at time 3), with all patients having baseline features (e.g. age, gender - at time 1), despite a few missing values.
Some patients have performed also a stress test (at time 2), with specific continous details (eg stress duration), but others haven't. Notably, those without the stress test are not missing at random, as typically a stress test is not performed in those who are very sick, or have electrocardiographic abnormalities). Yet, it would be very important to be able to capture all stress test details, as it generates several prognostically informing variables (eg rate pressure procudct, stress duration, maximum heart rate, and so forth).
What should I do to capture the information associated with stress test features?
A complete case analysis will of course exclude all those without a stress test (roughly 50%).
Is it reasonable to impute with mice the stress features among also those who did not undergo any stress test?
Or should I best create a factor variable such as stress_status (0- no stress, 1-stress with low tolerance, 2-stress with high tolerance, and so forth)?