I am trying to figure out the following. Could you please comment on this?
Goal is to compare survival between two groups. Let's assume we have data with one-year follow up and have a simple model for getting age-adjusted estimates:
time | status ~ group + age
Is it reasonable to run models with different follow-up lengths? E.g. 1, 2, 6 and 12 months? By reasonable, I mean does it give some extra or valuable information?
My understanding is as follows:
If this is a Cox model
If the assumption of proportional hazards is met with all follow-ups, there is no point run models with different follow-ups due to the PH assumption. For example, one group always has a constantly higher/lower hazard ratio.
If this is an Accelerated Failure Time (AFT) model
If the proportional hazards assumption is not met, I would use AFT. Is it now reasonable to run models with different follow-ups? For example, group A and B may have similar 1- and 3-month survival but patients in group B die more likely after the 3rd month.