Residual plot The LOGISTIC Procedure Model Information Data Set WORK.ASSAY Response Variable (Events) y Response Variable (Trials) n Model binary logit Optimization Technique Fisher's scoring Number of Observations Read 9 Number of Observations Used 9 Sum of Frequencies Read 266 Sum of Frequencies Used 266 Response Profile Ordered Binary Total Value Outcome Frequency 1 Event 172 2 Nonevent 94 Model Convergence Status Convergence criterion (GCONV=1E-8) satisfied. Deviance and Pearson Goodness-of-Fit Statistics Criterion Value DF Value/DF Pr > ChiSq Deviance 29.3462 7 4.1923 0.0001 Pearson 28.5630 7 4.0804 0.0002 Number of events/trials observations: 9 NOTE: The covariance matrix has been multiplied by the heterogeneity factor (Pearson Chi-Square / DF) 4.08043. Residual plot The LOGISTIC Procedure Model Fit Statistics Intercept Intercept and Criterion Only Covariates AIC 86.683 75.379 SC 90.266 82.546 -2 Log L 84.683 71.379 Testing Global Null Hypothesis: BETA=0 Test Chi-Square DF Pr > ChiSq Likelihood Ratio 13.3037 1 0.0003 Score 12.6609 1 0.0004 Wald 11.0165 1 0.0009 Analysis of Maximum Likelihood Estimates Standard Wald Parameter DF Estimate Error Chi-Square Pr > ChiSq Intercept 1 -15.8331 4.9230 10.3438 0.0013 logconc 1 5.5776 1.6804 11.0165 0.0009 Odds Ratio Estimates Point 95% Wald Effect Estimate Confidence Limits logconc 264.425 9.816 >999.999 Association of Predicted Probabilities and Observed Responses Percent Concordant 70.6 Somers' D 0.492 Percent Discordant 21.4 Gamma 0.535 Percent Tied 8.0 Tau-a 0.226 Pairs 16168 c 0.746