Lets say I have a dataset where I want to estimate the relative risk of outcome X based on a binary treatment level Y, using PROC GENMOD to fit a logistic regression model. I can use the BAYES statement to have SAS 9.2 produce nice, MCMC-based prior distributions for my data.
My question is, what if I then want to sample from that posterior distribution? For example, if I estimate a OR and its 95% credible interval for the effect of Y, and subsequently want to use that estimate in another analysis. If I wanted to perform a sensitivity analysis based on the possibility of error in my estimate of the effect of Y, it makes sense to just run a Monte Carlo simulation based on the distribution of Y. But in this case, rather than being a really straightforward random number generation, I need to pull from that prior.
Is the best way to do this using the OUTPOST option to get the data set of generated posterior samples and then just randomly sample from that new data set? Or is there some other, more clever mechanism I'm not seeing?