[gov2001-l] hi!

Hi, we are trying to get predicted values for a negative binomial model...we have our x mat, of observed values and some beta parameters (which we will draw from a mutivariate normal). our problem is the dispersion parameter, sigma squared....how do we draw that? so we should get one sigma squared per draw of k + 1 betas (k being the number of covariates), but we are a little confused...would sigma squared just be the variance of the mvrnorm distribution at each draw?? Then, how do we incorporate the sigma squared values into the link function? or is it the case that, when we are drawing our y's, we incorporate the mean of the draws of sigma squared values (so the mean of a 1000 values, right)?? thanks! best, sparsha