05-12-2013 07:37 PM
No idea, but it sounds more like survival analysis.
What doesn't survival analysis cover that you would want in ARIMA, some sort of seasonality?
05-12-2013 07:47 PM
I'm interested in investigating the effect of an intervention on readmission rate, after controlling for patient-level covariates. I have about 3 years of historical/pre-intervention data and 1.5 years of post-intervention data. I want to incorporate time trend to account for changes in medical practice over time and its relation with readmission.
05-13-2013 09:45 AM
That sounds, at least to me, more like a survival analysis with a time-dependent covariate, as proposed by @Reeza. Think about what the ARIMA model would be fitting--a long string of zeroes, a single 1, perhaps some more 1's (if you model as still admitted), then another long string of zeroes. That is not a good dataset for fitting an ARIMA model. Instead, time to re-admission, with a covariate that describes the intervention status, strikes me as something that would work. Check out PROC PHREG.
05-13-2013 11:04 AM
I would add some indicator variables, possible time dependent to account for the changes in practice.
You'll have to be careful with the pre-intervention/post-intervention data to make sure they're handled appropriately, but survival analysis is what you're looking for.
05-13-2013 11:23 AM
subjid date admission_status intervention_status covariate1 covariate2 (other covariates of interest).
That should set it up for a survival analysis, as per Example 67.7 Time-Dependent Repeated Measurements of a Covariate.