i have used nproc logistic and found this The LOGISTIC Procedure Model Information Data Set WORK.LBW Response Variable lbw Low Birth Weight Number of Response Levels 2 Model binary logit Optimization Technique Fisher's scoring Number of Observations Read 100 Number of Observations Used 100 Response Profile Ordered Value lbw Total Frequency 1 0 41 2 1 59 Probability modeled is lbw=1. Class Level Information Class Value Design Variables smoke 0 0 1 1 hypert 0 0 1 1 ui 0 0 1 1 Model Convergence Status Convergence criterion (GCONV=1E-8) satisfied. Model Fit Statistics Criterion Intercept Only Intercept and Covariates AIC 137.372 122.945 SC 139.977 143.786 -2 Log L 135.372 106.945 Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 28.4272 7 0.0002 Score 23.4810 7 0.0014 Wald 16.2887 7 0.0226 Type 3 Analysis of Effects Effect DF Wald Chi-Square Pr > ChiSq age 1 0.3192 0.5721 mweight 1 8.5850 0.0034 smoke 1 2.3197 0.1277 plabor 1 0.2534 0.6147 hypert 1 4.6578 0.0309 ui 1 5.2826 0.0215 visits 1 0.0904 0.7637 Analysis of Maximum Likelihood Estimates Parameter DF Estimate Standard Error Wald Chi-Square Pr > ChiSq Intercept 1 3.9132 1.5664 6.2407 0.0125 age 1 -0.0282 0.0499 0.3192 0.5721 mweight 1 -0.0288 0.00983 8.5850 0.0034 smoke 1 1 0.7444 0.4888 2.3197 0.1277 plabor 1 0.3045 0.6048 0.2534 0.6147 hypert 1 1 2.1484 0.9955 4.6578 0.0309 ui 1 1 2.6874 1.1693 5.2826 0.0215 visits 1 0.0683 0.2271 0.0904 0.7637 Odds Ratio Esti