I am trying to do a Time To Event analysis, looking at patients with Multiple Sclerosis, which can lead to wheelchair use.
My intended study is to look at the time from MS diagnosis to first Wheelchair use. I know that everyone in my cohort has MS before the join the cohort.
In most cases, I know the date of diagnosis exactly, in other cases, I know that the diagnosis was some time before they joined the cohort
I believe this means that the index date - the date of diagnosis - is sometimes left censored. How should I account for this in my analysis? Here is some example data:
So for example: We know that
Patient 1 was diagnosed in
1995, and we know that
Patient 2 was diagnosed some time before
Patient 1 started using a wheelchair in
Patient 2 did not use a wheelchair until at least
For right censored data, I know to differentiate censoring dates from event dates by using the
event argument in the
My question is: Is the situation I am describing above left censoring? As im talking about knowing the index date, not the event of interest date. and secondly, what is the appropriate way to do handle situations like this in survival analysis?
I want to be sure that I'm not confusing the concept of left censoring. the first time I would be able to observe the outcome event in question (wheelchair use) could be thought of as the left_censored date, however I want to account for a left censored index date.