Hi - hope this is the right location so here goes. I am interested in calculating the predicted probabilities for a binary-level outcome and using a categorical predictor (4-levels from 0-3). The Margins Macro appears to have what I need but, when I run the macro, the output does not include a Predictive Margins Table and there is a note that the "algorithm converged". Also no errors noted in the Log file. Any ideas on what I'm doing wrong? Program and output below. Many thanks. PROGRAM: %Margins (data = ecg.ECG_only_final, response = lad_axis,*BINARY VARIABLE WITH VALUES OF 1, 2; roptions = events='1', class = bp_htn,*MULTI-LEVEL VARIABLE WITH VALUES OF 0,1,2,3; model = bp_htn, dist = binomial, margins = bp_htn, options = diff cl); run; The GENMOD Procedure Model Information Data Set WORK._EXPDATA Distribution Binomial Link Function Logit Dependent Variable LAD_axis LAD_axis Number of Observations Read 729 Number of Observations Used 729 Number of Events 38 Number of Trials 729 Response Profile Ordered Value LAD_axis Total Frequency 1 1 38 2 0 691 PROC GENMOD is modeling the probability that LAD_axis='1'. One way to change this to model the probability that LAD_axis='0' is to specify the DESCENDING option in the PROC statement. Criteria For Assessing Goodness Of Fit Criterion DF Value Value/DF Log Likelihood -147.6443 Full Log Likelihood -147.6443 AIC (smaller is better) 303.2885 AICC (smaller is better) 303.3438 BIC (smaller is better) 321.6552 Algorithm converged. Analysis Of Maximum Likelihood Parameter Estimates Parameter DF Estimate Standard Error Wald 95% Confidence Limits Wald Chi-Square Pr > ChiSq Intercept 1 -2.6741 0.2585 -3.1808 -2.1675 107.04 <.0001 bp_htn_0 1 -0.6217 0.4129 -1.4310 0.1876 2.27 0.1322 bp_htn_1 1 0.0351 0.4171 -0.7824 0.8525 0.01 0.9329 bp_htn_2 1 -0.5245 0.7663 -2.0264 0.9774 0.47 0.4937 bp_htn_3 0 0.0000 0.0000 0.0000 0.0000 . . Scale 0 1.0000 0.0000 1.0000 1.0000 Note: The scale parameter was held fixed.
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