Hi, I would like to analyse a longitudinal data set with relatively many missing values using proc mcmc. Before moving to the "missingness issue", however, I am not sure how to implement an autoregessive covariance structure in proc mcmc. I have seen a few examples on unbalanced longitudinal data with proc mcmc, but they do not model the covariance structure explicitly. My data is in long format, of course, as the number of observations per subject varies. Now, to implement a specific covariance structure, I would need to define a multivariate distribution spanning multiple ROWS, would I not? None of the examples I could find tackles this problem. Either the data is balanced (then it can be brought to wide format and it is clear how to specify the covariance structure) or the covariance structure was not modeled explicitly. It would be great to get some hints as to whether this is possible with proc mcmc at all, and if so, which resources could help me understand how to implement this. Best, Kevin
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