Hi All,   I am using proc logistic to estimate propensity scores with the code below: proc logistic data=anh.anh_sample_sat2;     model tri_both (event='1')=race age bmi parity_1 any_smoke any_diabetes_oshpd htn_disorder non_cchd_sbd;     output out=anh.prop pred=ps;     title "Estimation of propensity score from covariates"; run;   Both my outcome and all covariates are binary (0/1)   Here is the model without the pscore: proc logistic data=anh.prop;     model cchd (event='1')=tri_both race age bmi parity_1 any_smoke any_diabetes_oshpd htn_disorder non_cchd_sbd ps;     title "Adding propensity score as covariate"; run;   and the model with the p-score added as a covariate: proc logistic data=anh.prop;     model cchd (event='1')=tri_both race age bmi parity_1 any_smoke any_diabetes_oshpd htn_disorder non_cchd_sbd;     title "Without propensity score as covariate"; run;     When I add the p-score I get output that I do not know how to interpret (see bold text below). Can someone please help me understand this? Thank you in advance!!! My outcome is rare (298/115,406) and again all variables are binary (0/1) Odds Ratio Estimates Effect Point Estimate 95% Wald Confidence Limits tri_both 1.410 1.080 1.840 race 1.018 0.671 1.545 age 1.264 0.599 2.666 bmi 0.952 0.393 2.309 parity_1 0.823 0.218 3.107 any_smoke 0.289 <0.001 550.733 any_diabetes_OSHPD 0.706 0.006 86.076 HTN_disorder 0.502 <0.001 >999.999 non_cchd_sbd 7.540 0.576 98.620 ps >999.999 <0.001 >999.999 ... View more