For some problems where the SE blows up, rescaling can help a lot.  I noticed that the sum of weights is 4.6 x 10**7 for ~5K records used, so you are talking about average weight per record of about 10,000.  So what happens if you divide all of your weights by 1000? Relative weights remain the same, and perhaps convergence and estimability can be improved. Of course, you have to remember this scaling when interpreting any results.   The other issue may be inconsistency in weights by class or strata. Potentially, you have 150 possible class levels (5x2x5x3), and if sample size and/or weighting are such that you consistently have very small values and very large values by class level, again you may find this sort of behavior.   Unfortunately, for the latter problem, I don't see an easy out, other than collapsing some class levels or eliminating one or more class variables.   SteveDenham ... View more