I am interested in knowing whether or not there is a consensus about the optimal way to analyze hospital length of stay (LOS) data from a RCT. This is typically a very right-skewed distribution, whereby most patients are discharged within a few days to a week, but the rest of the patients have quite unpredictable (and sometimes quite lengthy) stays, which form the right tail of the distribution.
Options for analysis include:
- t test (assumes normality which is not likely present)
- Mann Whitney U test
- logrank test
- Cox proportional hazards model conditioning on group allocation
Do any of these methods have demonstrably higher power?
Best Answer
I'm actually embarking on a project that does exactly this, although with observational, rather than clinical data. My thoughts have been that because of the unusual shape of most length of stay data, and the really well characterized time scale (you know both the origin and exit time essentially perfectly), the question lends itself really well to survival analysis of some sort. Three options to consider: