Model 1: ROC Curve for Model Area Under the Curve = 0.7282 Testing Global Null Hypothesis: BETA=0 1.00 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 5.6150 1 0.0178 Score 6.3451 0.0118 0.75 Wald 5.7206 0.0168 Analysis of Maximum Likelihood Estimates Sensitivity 0.50 Standard Wald Parameter DF Estimate Error Chi-Square Pr > ChiSq Intercept -0.3037 0.6191 0.2407 0.6237 0.25 apgar5 1 -0.2496 0.1044 6.7206 0.0168 Odds Ratio Estimates 0.00 95% Wald Effect Point Estimate Confidence Limits 0.00 0.25 0.50 0.75 1.00 apgar5 0.779 0.635 0.956 1 - Specificity Model 2: Testing Global Null Hypothesis: BETA=0 ROC Curve for Model Test Chi-Square DF Pr > ChiSq Area Under the Curve = 0.6020 Likelihood Ratio 2.2478 0.1338 1.00 Score 2.1518 0.1424 Wald 2.0583 0.1514 0.75 Analysis of Maximum Likelihood Estimates Standard Wald Sensitivity 0.50 Parameter DF Estimate Error Chi-Square Pr > ChiSq Intercept -1.4088 0.3363 17.5427 <.0001 odds ratio estimates wald effect point estimate confidence limits d.oc sex specificity model roc curve for area under the testing global null hypothesis: beta="0" test chi-square df pr> ChiSq Likelihood Ratio 7.5762 2 0.0226 Score 8.1478 2 0.0170 Wald 7.1446 2 0.0281 0.75 Analysis of Maximum Likelihood Estimates Standard Wald Parameter DF Estimate Error Chi-Square Pr > ChiSq Sensitivity 0.50 Intercept -0.0134 0.6596 0.0004 0.9838 apgar5 -0.2451 0.1056 5.3927 0.0202 -0.8622 0.6399 1.8152 0.1779 0.25 Odds Ratio Estimates 95% Wald Effect Point Estimate Confidence Limits 0.00 apgar5 0.783 0.636 0.96 0.00 0.25 0.50 0.75 1.00 0.422 0.120 1.480 1 - Specificity