Hi - Has anyone seen models for or tried doing a survival analysis when
for some observations the data had been observed after the event already
occurred? For example, trying to predict time to heart attack given some
ECG measurements, but for some patients, the measurements were obtained
after the patient already had been in the hospital after the attack. So
in one sense the time to event is actually negative and censored at
zero. Probably a better approach would be some sort of
discrete/continuous mixture model where with a certain probability, the
event has already occurred and given that it hasn't, a standard survival
model takes effect.
Al Feiveson
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