Hi, I wanted to add one more thing to this. We have submitted another paper using the same dataset in a different journal. Here we were looking for association between outcome-prescription and different variables patient characteristics including age , gender, ethnicity , history of alcohol abuse etc. , provider characteristic including provider's age, gender , year of practice. We did mutivariate linear regression Proc GLM and found that patient age, gender, ethnicity, surgeon gender, age, and years in practice was significantly predictive of the amount of opioids prescribed. We have received a comment from reviewer saying, 'My major concern in the paper is the way that surgeon characteristics are incorporated in the models. There is likely significant clustering by surgeon and thus inclusion of just the characteristics without adjusting for clustering may incorrectly measure the effect of the surgeon predictors on the outcome. A multi-level model (with patient and surgeon-levels) would be more appropriate and account for clustering effects. ' Plaese let me know what do you think about this. N= 23000 and number of surgeons= 90
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