Survival analysis is not my usual territory and so I would appreciate some advice.
I have data on around 5,700 residents of aged care facilities enrolled into a study on the effect of an intervention delivered to the facilities for the benefit of residents. There were around 90 facilities randomised to control or intervention. We wish to assess the effect of the intervention in preventing certain events. The analysis plan included a survival analysis. We can resolve time to days (or hours/minutes with some assumptions) over a period of 18 months of observation.
Part of my problem is that about 35% (I am guessing - the data are at work - but it was a lot) of the residents either changed facility (often moving to higher care) or had time out from the facility (eg hospitalisation) or both. The other part is that those residents who changed facility, especially from low to high care were much more likely to experience the events of interest; presumably they were moved having been assessed as being at higher risk. If I were to say that those who changed facility were no longer under observation then I loose about 60% (again a guestimate - but reasonable) of events!
Complicating matters is that residents who moved may have moved from an intervention facility to a control facility or vice versa. Those moving from intervention to control could carry some of the impact of the intervention to the new facility - eg fitness or medication regimen, while those moving from a control facility to an intervention facility may obtain new benefit from the change (caveat: providing the intervention is working). Residents could move in and out of the same facility several times or change locations completely several times. There is also a wide age range to account for with older residents being at greater risk of experiencing any event.
My questions are:
1. What would be the best way to estimate the impact or not of the intervention?
2. How do/can I treat resident movements in a survival analysis?
3. As age is a risk factor, should age be the measure of time?
With respect to question 1, I am thinking that a logistic regression with the outcome being the event of interest and having several covariates describing movements could be one appropriate analysis - but I am not sure that would be best. ...
I am not sure how to answer question 2. I have done some reading around but nothing has lept out at me yet. One idea is to model final facility adjusting for origin (intervention or control and relative time), number of movements in and out of hospital and say number of facility changes. Another idea is to model initial facility, time in a control facility, time in an intervention facility, number of hospitalisations (ignoring time out). So many options, but they may be naive.
Advice and suggestions will be greatly appreciated.
Richard
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