Thanks for the quick response, and the simulation! Once the model is developed I intended to use PLM to make predictions under multiple scenarios where the term A is varied and then assess the difference in the exceedence frequency for each scenario using a cutpoint value. So for instance, if the cutpoint for identifying an exceedence is 0.50, then for row 239 the BLUP value is greater than 0.50 while the NOBLUP value is less than 0.50. In my case this makes a fairly substantial difference but now I am thinking that this means I should probably specify D as a fixed effect even though the overall objective is to evaluate the effects of A. ... View more

Thanks. My confusion is how to interpret these two predictions. Seems to me that they are both marginal predicted probabilities without including the random effect. SAS has the option for prediction without random effect (noblup), even one specified random effect. ... View more

The "L'Beta Estimate" and "Standard error" values, and the "L'Beta Confidence limits" in the ESTIMATE statement results are on the logit scale (log[p/(1-p)]) when fitting a logistic model. For an ESTIMATE statement that defines a difference in two logits, using the EXP option provides the odds ratio estimate and its confidence limits. Equivalently, you can use an LSMEANS statement along with the DIFF, ODDSRATIO, and CL options. For example, using the GEE example in the Getting Started section of the GENMOD documentation, adding these statements provides the odds ratio estimate and confidence interval for comparing the two cities:   estimate 'city' city 1 -1 / exp; lsmeans city / diff oddsratio cl;   However, a standard error on the odds ratio scale is not available.   ... View more

Thank you! I will look into it.   ... View more