Luke,    Try adding an lsmeans statement to your model, to see if you get proportions out that you can understand.  Also, using by subject processing can greatly improve your chances of convergence.  I have rewritten your random statement to take advantage of this. proc glimmix data=rcb ; class site species mulch herb seedling ; model Alive (event='1') = mulch herb species mulch*herb mulch*species herb*species mulch*herb*species/s dist=binary link=logit; random intercept mulch herb species mulch*herb mulch*species herb*species /subject=site s; lsmeans mulch|herb|species/diff ilink; run; Now, i would also suggest that perhaps your random statement probably overspecifies the number of random effects.  You could probably get by with:   random intercept/subject=site;   Also, you should consider some points brought out by Walt Stroup in his book Generalized Linear Mixed Models (get a copy)--that the estimates and tests from this method tend to be biased, and that you may want to consider adding METHOD=LAPLACE to the PROC GLIMMIX statement.   Steve Denham ... View more