I have data on the closure of brands of stores and I would like to model the factors that influence the risk of closure. I know all the stores that are open on a certain date, 1st January 2015 (but they may have actually opened for example 5, 10, 20 or 30 years ago). I know the month of closure up until 21st December 2021. For covariates I am using information such as the catchment population, distances to competitor stores and distance to stores of the same brand. These vary by year. To model the outcome of store closure I am proposing to use Cox proportional hazard models in R using package
survival. Because all stores are open on the 1st January 2015 I have an unusual form of right censoring in that the survival time I observe for each store is at least the time to the month in which they closed or 84 months (7*12) (see this post : Misconception about left censoring).
My question is that in models of such a form, information is used on the survival time and an indication of censoring (traditionally 0=censored, survived; 1=non-censored, eg died). Since all my observations are right censored in some sense, does this mean that this indication of censoring is the same for all stores?