My data are hospital cost data and I model them as a function of various cost drivers. I need to specify random effects and a lognormal or gamma distribution for my data, therefore I found proc glimmix convenient.My model converges with a lognormal distribution and link=id. I found it very difficult to interprete the parameter estimates. An OLS regression without any explanatory variables renders an intercept of around 77,000. My Glimmix model renders an intercept of about 10,500 (regardless of covariates and random effects). Clearly exponentiating brings these parameters close to the 'true' figure but firstly I can't find any literature telling me to exponentiate and secondly all parameters turn positive when exponentiating. I've spent some time on the internet trying to find solutions. I hope you can help. Thanx
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