Hello, I am using proc logistic (binary logit model). I would like to see if I can get the same predicted probability IP_1 values that proc logistic provides, if I do the calculation manually using regression equation. I tried Probability = 1 / [1 +exp (-(B0 + b1X))] and inputted the values from the “Estimate” column and the values for my variables, but the resulting probability was not the same with what I got in IP_1 column. I tried using reference coding instead of effect coding to get the estimates, and then calculated the probability, but again it was not the same with IP_1 value. How can I get to IP_1 = 0.000406? Here is an example with the values of the variables, and coefficients. var1 var2 var3 var4 IP_1 manual calculation 21 1897 0 0 0.000406 0.000228 Estimates with effect coding Parameter DF Estimate Intercept 1 -6.4624 var3 0 1 0.6089 var4 0 1 -0.038 var2 1 -0.00089 var1 1 -0.0111 Estimates with reference coding Parameter DF Estimate Intercept 1 -7.0333 var3 0 1 1.2178 var4 0 1 -0.076 var2 1 -0.00089 var1 1 -0.0111 proc logistic data=mydata desc outmodel= model plots(only)=roc PLOTS(MAXPOINTS=NONE) plots=effect; class var3 (ref='1') var4 (ref='1') / param = ref ; model target_var = var1 var2 var3 var4 / lackfit firth ctable pprob=(0.0010, 0.0015, 0.002, 0.0025, 0.003, 0.004) maxiter=100; output out=preds predprobs=individual; run; Thank you. Zeynep
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