Dear all, I am running into a big problem trying to have administrative region fixed effects and account for cluster robust standard error. The datset i am using for the research collects data using multiple- stage sampling. The sampling of clusters in districts, communes, enumeration areas at the first stage and then selecting households within each cluster represents multiple-stage stratified sampling design which is not perfectly random. This would underestimate my SE and I would like to have robust standard error in the model to fix the problem. The model I run: proc genmod data=xlucky descending ; class districtid(param=ref); model (Binary Dependent Variable) = (explanatory variables) / dist=binary link =logit ; repeated subject=districtid/type=cs corrw; run; This code give me all the parameter estimates and robust standard errors. HOWEVER, when I run: proc genmod data=xlucky descending ; class districtid(param=ref); model (Binary Dependent Variable) = (explanatory variables districtid) / dist=binary link =logit ; repeated subject=districtid/type=cs corrw; run; To have fixed effect and the RSE, the error massage pops up: WARNING: The negative of the Hessian is not positive definite. The convergence is questionable. WARNING: The procedure is continuing but the validity of the model fit is questionable. WARNING: The specified model did not converge. Any idea how to get this right? Same problem happens when I run proc glimmix. Thank you for your help. WL
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