I am working with Hospital Length of stay data for the first time. It is highly right skewed. In researching ways to approach this problem, I thought a survival model fits the problem description.
The dependent variable is the waiting time until the occurrence of a well-defined event, observations are censored, in the sense that for some units the event of interest has not occurred at the time the data are analyzed, there are predictors or explanatory variables whose effect on the waiting time we wish to asses or control. http://data.princeton.edu/wws509/notes/c7.pdf
I was wondering what kind of assumptions go in to this kind of model, as opposed to say a Poisson regression, another alternative I was looking in to?
Is there any assumptions that need to be made about the distributions of the independent variables? What about how those variables change with respect to time?