ODDSRATIO provide below OR. I believe this is the same as the ORs from LSMEANS.     How to choose reference group from both variables (i.e. procedure indication=non-diagnostic / cci=0) and use all levels of one interaction term across the other interaction variable (i.e. procedure indication=EGD with all levels of CCI) to output OR?   Odds Ratio Estimates and Wald Confidence Intervals Odds Ratio Estimate 95% Confidence Limits p-Value proc_ind EGD vs diagnostic at cci=>=3 2.089 0.977 4.465 0.0573 proc_ind EGD vs non-diagnostic at cci=>=3 1.544 0.909 2.622 0.1082 proc_ind diagnostic vs non-diagnostic at cci=>=3 0.739 0.327 1.669 0.4669 proc_ind EGD vs diagnostic at cci=1-2 2.325 1.336 4.046 0.0028 proc_ind EGD vs non-diagnostic at cci=1-2 1.276 0.894 1.820 0.1789 proc_ind diagnostic vs non-diagnostic at cci=1-2 0.549 0.318 0.948 0.0314 proc_ind EGD vs diagnostic at cci=0 1.775 1.215 2.593 0.0030 proc_ind EGD vs non-diagnostic at cci=0 2.315 1.643 3.262 <.0001 proc_ind diagnostic vs non-diagnostic at cci=0 1.304 0.881 1.930 0.1841   SLICE gives below: Chi-Square Test for proc_ind*cci Least Squares Means Slice Slice Num DF Chi-Square Pr > ChiSq proc_ind EGD 2 0.54 0.7629   Simple Differences of proc_ind*cci Least Squares Means Slice cci _cci Estimate Standard Error z Value Pr > |z| Alpha Lower Upper Odds Ratio Lower Confidence Limit for Odds Ratio Upper Confidence Limit for Odds Ratio proc_ind EGD >=3 1-2 0.1230 0.2075 0.59 0.5536 0.05 -0.2838 0.5297 1.131 0.753 1.698 proc_ind EGD >=3 0 0.1525 0.2168 0.70 0.4816 0.05 -0.2723 0.5774 1.165 0.762 1.781 proc_ind EGD 1-2 0 0.02960 0.1905 0.16 0.8765 0.05 -0.3437 0.4029 1.030 0.709 1.496 ... View more

Thanks, Reeza. I did ODDSRATIO, SLICE, and LSMEANS. but none of them give the OR I need. Here is the code.    proc logistic data=model; class &mv1 / param=glm order=internal; model sed(event="1")= &mv1 proc_ind*cci; oddsratio proc_ind / at (cci=all); slice proc_ind*cci / diff oddsratio cl; lsmeans proc_ind*cci / ilink diff oddsratio cl; run;   Thanks! ... View more