First off, the noiter means that the values are the initial starting values, so things are dicey when you ask 'valid'.  The results (esp. the standard errors of the lsmeans) essentially do not recognize the random effects. What you have is quasi-separation.  For the lowest value of lat, it is all zeroes. It appears that your data are on an individual basis (0/1).  If that is the case, change the distribution to dist=binary.  The other possibility is to aggregate within line, so that a binomial (x/y) value is analyzed. If the distribution is kept as binary, you might also have better luck if you add an NLOPTIONS statement, and set the technique to something other than the default quasi-newton.  I have had pretty good luck with ridged newton-raphson, so the line would look like: nloptions tech=nrridg; Still, quasi-separation is a big problem with generalized linear models, but Google is your friend, and there are a lot of sites out there with other suggestions. Also, check the following thread: https://communities.sas.com/message/130974.  The suggestion there to group Age into buckets could be translated to group lat into buckets.  Of course, that would mean grouping Panama with something else and defeating the purpose of your analysis.  So perhaps grouping within line and using dist=binomial might help. Steve Denham ... View more