I'm new to the listserv and unfortunately don't have access to the northwestern archive for this listserv as it appears to require login/pw, so I apologize if this question has been asked before.
I'm performing multiple imputation on a rather large dataset (~450,000 obs) with about 9% overall missingness. I was getting "failure to converge" errors initially. This resolved when I removed some variables. Oddly enough though, I found a mistake in my coding of one variable and reworked the entire dataset, and now no longer get the error at all. I believe my original error was related to very unbalanced binary/categorical variables (<2% in a category), partly because of the reference white paper by Gullion, Chen, Meltesen (Applied aspects of using multiple imputation in clinical data). It seemed that removal of these types of variables eliminated the error message, but it was unclear why one variable vs another that both had sparse categories (or the dummy variable set equivalent). Are there other plausible explanations for receiving this error in proc MI? and are there common methods to troubleshoot such an error when it does occur? thank you for any advice you can provide, - mike -------------------------- Michael Liao, MD Clinical Research Fellow Department of Emergency Medicine Denver Health Medical Center
