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Results: Binary Logistic Regression

The LOGISTIC Procedure

Model Information

Model Information
Data Set MYLIB.SURVEYMONKEY  
Response Variable Price Price
Number of Response Levels 2  
Model binary logit  
Optimization Technique Fisher's scoring  

Observations Summary

Number of Observations Read 135
Number of Observations Used 135

Response Profile

Response Profile
Ordered
Value		 Price Total
Frequency
1 0 15
2 1 120

Probability modeled is Price='1'.

Convergence Status

Model Convergence Status
Convergence criterion (GCONV=1E-8) satisfied.

Fit Statistics

Model Fit Statistics
Criterion Intercept Only Intercept and Covariates
AIC 96.185 88.767
SC 99.090 117.820
-2 Log L 94.185 68.767

Global Tests

Testing Global Null Hypothesis: BETA=0
Test Chi-Square DF Pr > ChiSq
Likelihood Ratio 25.4175 9 0.0025
Score 23.1796 9 0.0058
Wald 15.2308 9 0.0848

Parameter Estimates

Analysis of Maximum Likelihood Estimates
Parameter DF Estimate Standard
Error		 Wald
Chi-Square		 Pr > ChiSq
Intercept 1 1.0001 2.5494 0.1539 0.6948
Age 1 0.00549 0.0751 0.0053 0.9417
Price per night 1 -0.0128 0.00465 7.5461 0.0060
Safety 1 -0.1077 0.2251 0.2287 0.6325
Travel Frequency 1 0.2404 0.1366 3.0994 0.0783
Close to tourist att 1 -0.00255 0.9361 0.0000 0.9978
Housekeeping 1 -4.0055 1.5191 6.9523 0.0084
Number of Rooms 1 -0.8505 1.3237 0.4128 0.5205
Hotel Rewards 1 -1.0492 0.8848 1.4061 0.2357
Count 1 0.9945 0.3786 6.9014 0.0086

Odds Ratios

Odds Ratio Estimates
Effect Point Estimate 95% Wald
Confidence Limits
Age 1.006 0.868 1.165
Price per night 0.987 0.978 0.996
Safety 0.898 0.578 1.396
Travel Frequency 1.272 0.973 1.662
Close to tourist att 0.997 0.159 6.247
Housekeeping 0.018 <0.001 0.358
Number of Rooms 0.427 0.032 5.719
Hotel Rewards 0.350 0.062 1.984
Count 2.703 1.287 5.677

Odds Ratios with 95% Wald Confidence Limits

Odds Ratio Estimate = 2.7033 COMPBL(_EFFECT) = Count Odds Ratio Estimate = 0.3502 COMPBL(_EFFECT) = Hotel Rewards Odds Ratio Estimate = 0.4272 COMPBL(_EFFECT) = Number of Rooms Odds Ratio Estimate = 0.0182 COMPBL(_EFFECT) = Housekeeping Odds Ratio Estimate = 0.9975 COMPBL(_EFFECT) = Close to tourist att Odds Ratio Estimate = 1.2718 COMPBL(_EFFECT) = Travel Frequency Odds Ratio Estimate = 0.8979 COMPBL(_EFFECT) = Safety Odds Ratio Estimate = 0.9873 COMPBL(_EFFECT) = Price per night Odds Ratio Estimate = 1.0055 COMPBL(_EFFECT) = Age COMPBL(_EFFECT) = Count Upper = 5.677 Lower = 1.2873 COMPBL(_EFFECT) = Count Upper = 5.677 Lower = 1.2873 COMPBL(_EFFECT) = Count Upper = 5.677 Lower = 1.2873 COMPBL(_EFFECT) = Hotel Rewards Upper = 1.9838 Lower = 0.0618 COMPBL(_EFFECT) = Hotel Rewards Upper = 1.9838 Lower = 0.0618 COMPBL(_EFFECT) = Hotel Rewards Upper = 1.9838 Lower = 0.0618 COMPBL(_EFFECT) = Number of Rooms Upper = 5.7193 Lower = 0.0319 COMPBL(_EFFECT) = Number of Rooms Upper = 5.7193 Lower = 0.0319 COMPBL(_EFFECT) = Number of Rooms Upper = 5.7193 Lower = 0.0319 COMPBL(_EFFECT) = Housekeeping Upper = 0.3577 Lower = .00093 COMPBL(_EFFECT) = Housekeeping Upper = 0.3577 Lower = .00093 COMPBL(_EFFECT) = Housekeeping Upper = 0.3577 Lower = .00093 COMPBL(_EFFECT) = Close to tourist att Upper = 6.2469 Lower = 0.1593 COMPBL(_EFFECT) = Close to tourist att Upper = 6.2469 Lower = 0.1593 COMPBL(_EFFECT) = Close to tourist att Upper = 6.2469 Lower = 0.1593 COMPBL(_EFFECT) = Close to tourist att Upper = 6.2469 Lower = 0.1593 COMPBL(_EFFECT) = Travel Frequency Upper = 1.6621 Lower = 0.9731 COMPBL(_EFFECT) = Travel Frequency Upper = 1.6621 Lower = 0.9731 COMPBL(_EFFECT) = Travel Frequency Upper = 1.6621 Lower = 0.9731 COMPBL(_EFFECT) = Safety Upper = 1.3959 Lower = 0.5776 COMPBL(_EFFECT) = Safety Upper = 1.3959 Lower = 0.5776 COMPBL(_EFFECT) = Safety Upper = 1.3959 Lower = 0.5776 COMPBL(_EFFECT) = Price per night Upper = 0.9963 Lower = 0.9783 COMPBL(_EFFECT) = Age Upper = 1.1649 Lower = 0.8679 COMPBL(_EFFECT) = Age Upper = 1.1649 Lower = 0.8679 COMPBL(_EFFECT) = Age Upper = 1.1649 Lower = 0.8679 X = 1 COMPBL(_EFFECT) = Count COMPBL(_EFFECT) = Hotel Rewards COMPBL(_EFFECT) = Number of Rooms COMPBL(_EFFECT) = Housekeeping COMPBL(_EFFECT) = Close to tourist att COMPBL(_EFFECT) = Travel Frequency COMPBL(_EFFECT) = Safety COMPBL(_EFFECT) = Price per night COMPBL(_EFFECT) = Age
Plot of Odds Ratios with 95% Wald Confidence Limits

Association Statistics

Association of Predicted Probabilities and Observed Responses
Percent Concordant 84.2 Somers' D 0.686
Percent Discordant 15.7 Gamma 0.686
Percent Tied 0.1 Tau-a 0.136
Pairs 1800 c 0.843

ROC Curve

Model = Model (0.8428) Sensitivity = 1 1 - Specificity = 1 Frequency = 1 Positive Predictive Value = 0.8889 Negative Predictive Value = . Probability Level = 0.1248 Model = Model (0.8428) Sensitivity = 1 1 - Specificity = 0.9333 Frequency = 1 Positive Predictive Value = 0.8955 Negative Predictive Value = 1 Probability Level = 0.2106 Model = Model (0.8428) Sensitivity = 1 1 - Specificity = 0.9333 Frequency = 1 Positive Predictive Value = 0.8955 Negative Predictive Value = 1 Probability Level = 0.2106 Model = Model (0.8428) Sensitivity = 1 1 - Specificity = 0.8667 Frequency = 1 Positive Predictive Value = 0.9023 Negative Predictive Value = 1 Probability Level = 0.3069 Model = Model (0.8428) Sensitivity = 1 1 - Specificity = 0.8667 Frequency = 1 Positive Predictive Value = 0.9023 Negative Predictive Value = 1 Probability Level = 0.3069 Model = Model (0.8428) Sensitivity = 1 1 - Specificity = 0.8 Frequency = 1 Positive Predictive Value = 0.9091 Negative Predictive Value = 1 Probability Level = 0.4429 Model = Model (0.8428) Sensitivity = 1 1 - Specificity = 0.8 Frequency = 1 Positive Predictive Value = 0.9091 Negative Predictive Value = 1 Probability Level = 0.4429 Model = Model (0.8428) Sensitivity = 0.9917 1 - Specificity = 0.8 Frequency = 1 Positive Predictive Value = 0.9084 Negative Predictive Value = 0.75 Probability Level = 0.5001 Model = Model (0.8428) Sensitivity = 0.9917 1 - Specificity = 0.8 Frequency = 1 Positive Predictive Value = 0.9084 Negative Predictive Value = 0.75 Probability Level = 0.5001 Model = Model (0.8428) Sensitivity = 0.9833 1 - Specificity = 0.8 Frequency = 1 Positive Predictive Value = 0.9077 Negative Predictive Value = 0.6 Probability Level = 0.5346 Model = Model (0.8428) Sensitivity = 0.9833 1 - Specificity = 0.8 Frequency = 1 Positive Predictive Value = 0.9077 Negative Predictive Value = 0.6 Probability Level = 0.5346 Model = Model (0.8428) Sensitivity = 0.9833 1 - Specificity = 0.7333 Frequency = 1 Positive Predictive Value = 0.9147 Negative Predictive Value = 0.6667 Probability Level = 0.5761 Model = Model (0.8428) Sensitivity = 0.9833 1 - Specificity = 0.7333 Frequency = 1 Positive Predictive Value = 0.9147 Negative Predictive Value = 0.6667 Probability Level = 0.5761 Model = Model (0.8428) Sensitivity = 0.9833 1 - Specificity = 0.6667 Frequency = 1 Positive Predictive Value = 0.9219 Negative Predictive Value = 0.7143 Probability Level = 0.6088 Model = Model (0.8428) Sensitivity = 0.9833 1 - Specificity = 0.6667 Frequency = 1 Positive Predictive Value = 0.9219 Negative Predictive Value = 0.7143 Probability Level = 0.6088 Model = Model (0.8428) Sensitivity = 0.975 1 - Specificity = 0.6667 Frequency = 2 Positive Predictive Value = 0.9213 Negative Predictive Value = 0.625 Probability Level = 0.6273 Model = Model (0.8428) Sensitivity = 0.975 1 - Specificity = 0.6667 Frequency = 2 Positive Predictive Value = 0.9213 Negative Predictive Value = 0.625 Probability Level = 0.6273 Model = Model (0.8428) Sensitivity = 0.9667 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.928 Negative Predictive Value = 0.6 Probability Level = 0.639 Model = Model (0.8428) Sensitivity = 0.9667 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.928 Negative Predictive Value = 0.6 Probability Level = 0.639 Model = Model (0.8428) Sensitivity = 0.9583 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9274 Negative Predictive Value = 0.5455 Probability Level = 0.6521 Model = Model (0.8428) Sensitivity = 0.9583 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9274 Negative Predictive Value = 0.5455 Probability Level = 0.6521 Model = Model (0.8428) Sensitivity = 0.95 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9268 Negative Predictive Value = 0.5 Probability Level = 0.673 Model = Model (0.8428) Sensitivity = 0.95 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9268 Negative Predictive Value = 0.5 Probability Level = 0.673 Model = Model (0.8428) Sensitivity = 0.9417 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9262 Negative Predictive Value = 0.4615 Probability Level = 0.7096 Model = Model (0.8428) Sensitivity = 0.9417 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9262 Negative Predictive Value = 0.4615 Probability Level = 0.7096 Model = Model (0.8428) Sensitivity = 0.9333 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9256 Negative Predictive Value = 0.4286 Probability Level = 0.7223 Model = Model (0.8428) Sensitivity = 0.9333 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9256 Negative Predictive Value = 0.4286 Probability Level = 0.7223 Model = Model (0.8428) Sensitivity = 0.925 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.925 Negative Predictive Value = 0.4 Probability Level = 0.7419 Model = Model (0.8428) Sensitivity = 0.925 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.925 Negative Predictive Value = 0.4 Probability Level = 0.7419 Model = Model (0.8428) Sensitivity = 0.9167 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9244 Negative Predictive Value = 0.375 Probability Level = 0.7504 Model = Model (0.8428) Sensitivity = 0.9167 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9244 Negative Predictive Value = 0.375 Probability Level = 0.7504 Model = Model (0.8428) Sensitivity = 0.9083 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9237 Negative Predictive Value = 0.3529 Probability Level = 0.7737 Model = Model (0.8428) Sensitivity = 0.9083 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9237 Negative Predictive Value = 0.3529 Probability Level = 0.7737 Model = Model (0.8428) Sensitivity = 0.9 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9231 Negative Predictive Value = 0.3333 Probability Level = 0.785 Model = Model (0.8428) Sensitivity = 0.9 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9231 Negative Predictive Value = 0.3333 Probability Level = 0.785 Model = Model (0.8428) Sensitivity = 0.8917 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9224 Negative Predictive Value = 0.3158 Probability Level = 0.7907 Model = Model (0.8428) Sensitivity = 0.8917 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9224 Negative Predictive Value = 0.3158 Probability Level = 0.7907 Model = Model (0.8428) Sensitivity = 0.8833 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9217 Negative Predictive Value = 0.3 Probability Level = 0.8025 Model = Model (0.8428) Sensitivity = 0.8833 1 - Specificity = 0.6 Frequency = 1 Positive Predictive Value = 0.9217 Negative Predictive Value = 0.3 Probability Level = 0.8025 Model = Model (0.8428) Sensitivity = 0.8833 1 - Specificity = 0.5333 Frequency = 2 Positive Predictive Value = 0.9298 Negative Predictive Value = 0.3333 Probability Level = 0.803 Model = Model (0.8428) Sensitivity = 0.8833 1 - Specificity = 0.5333 Frequency = 2 Positive Predictive Value = 0.9298 Negative Predictive Value = 0.3333 Probability Level = 0.803 Model = Model (0.8428) Sensitivity = 0.875 1 - Specificity = 0.4667 Frequency = 1 Positive Predictive Value = 0.9375 Negative Predictive Value = 0.3478 Probability Level = 0.8072 Model = Model (0.8428) Sensitivity = 0.875 1 - Specificity = 0.4667 Frequency = 1 Positive Predictive Value = 0.9375 Negative Predictive Value = 0.3478 Probability Level = 0.8072 Model = Model (0.8428) Sensitivity = 0.875 1 - Specificity = 0.4 Frequency = 1 Positive Predictive Value = 0.9459 Negative Predictive Value = 0.375 Probability Level = 0.8115 Model = Model (0.8428) Sensitivity = 0.875 1 - Specificity = 0.4 Frequency = 1 Positive Predictive Value = 0.9459 Negative Predictive Value = 0.375 Probability Level = 0.8115 Model = Model (0.8428) Sensitivity = 0.8667 1 - Specificity = 0.4 Frequency = 1 Positive Predictive Value = 0.9455 Negative Predictive Value = 0.36 Probability Level = 0.817 Model = Model (0.8428) Sensitivity = 0.8667 1 - Specificity = 0.4 Frequency = 1 Positive Predictive Value = 0.9455 Negative Predictive Value = 0.36 Probability Level = 0.817 Model = Model (0.8428) Sensitivity = 0.8583 1 - Specificity = 0.4 Frequency = 1 Positive Predictive Value = 0.945 Negative Predictive Value = 0.3462 Probability Level = 0.8198 Model = Model (0.8428) Sensitivity = 0.8583 1 - Specificity = 0.4 Frequency = 1 Positive Predictive Value = 0.945 Negative Predictive Value = 0.3462 Probability Level = 0.8198 Model = Model (0.8428) Sensitivity = 0.85 1 - Specificity = 0.4 Frequency = 2 Positive Predictive Value = 0.9444 Negative Predictive Value = 0.3333 Probability Level = 0.8201 Model = Model (0.8428) Sensitivity = 0.85 1 - Specificity = 0.4 Frequency = 2 Positive Predictive Value = 0.9444 Negative Predictive Value = 0.3333 Probability Level = 0.8201 Model = Model (0.8428) Sensitivity = 0.8333 1 - Specificity = 0.4 Frequency = 1 Positive Predictive Value = 0.9434 Negative Predictive Value = 0.3103 Probability Level = 0.8274 Model = Model (0.8428) Sensitivity = 0.8333 1 - Specificity = 0.4 Frequency = 1 Positive Predictive Value = 0.9434 Negative Predictive Value = 0.3103 Probability Level = 0.8274 Model = Model (0.8428) Sensitivity = 0.8333 1 - Specificity = 0.3333 Frequency = 2 Positive Predictive Value = 0.9524 Negative Predictive Value = 0.3333 Probability Level = 0.8341 Model = Model (0.8428) Sensitivity = 0.8333 1 - Specificity = 0.3333 Frequency = 2 Positive Predictive Value = 0.9524 Negative Predictive Value = 0.3333 Probability Level = 0.8341 Model = Model (0.8428) Sensitivity = 0.8167 1 - Specificity = 0.3333 Frequency = 2 Positive Predictive Value = 0.9515 Negative Predictive Value = 0.3125 Probability Level = 0.8413 Model = Model (0.8428) Sensitivity = 0.8167 1 - Specificity = 0.3333 Frequency = 2 Positive Predictive Value = 0.9515 Negative Predictive Value = 0.3125 Probability Level = 0.8413 Model = Model (0.8428) Sensitivity = 0.8 1 - Specificity = 0.3333 Frequency = 1 Positive Predictive Value = 0.9505 Negative Predictive Value = 0.2941 Probability Level = 0.8449 Model = Model (0.8428) Sensitivity = 0.8 1 - Specificity = 0.3333 Frequency = 1 Positive Predictive Value = 0.9505 Negative Predictive Value = 0.2941 Probability Level = 0.8449 Model = Model (0.8428) Sensitivity = 0.7917 1 - Specificity = 0.3333 Frequency = 1 Positive Predictive Value = 0.95 Negative Predictive Value = 0.2857 Probability Level = 0.8545 Model = Model (0.8428) Sensitivity = 0.7917 1 - Specificity = 0.3333 Frequency = 1 Positive Predictive Value = 0.95 Negative Predictive Value = 0.2857 Probability Level = 0.8545 Model = Model (0.8428) Sensitivity = 0.7917 1 - Specificity = 0.2667 Frequency = 1 Positive Predictive Value = 0.9596 Negative Predictive Value = 0.3056 Probability Level = 0.8656 Model = Model (0.8428) Sensitivity = 0.7917 1 - Specificity = 0.2667 Frequency = 1 Positive Predictive Value = 0.9596 Negative Predictive Value = 0.3056 Probability Level = 0.8656 Model = Model (0.8428) Sensitivity = 0.7917 1 - Specificity = 0.2 Frequency = 1 Positive Predictive Value = 0.9694 Negative Predictive Value = 0.3243 Probability Level = 0.8661 Model = Model (0.8428) Sensitivity = 0.7917 1 - Specificity = 0.2 Frequency = 1 Positive Predictive Value = 0.9694 Negative Predictive Value = 0.3243 Probability Level = 0.8661 Model = Model (0.8428) Sensitivity = 0.7833 1 - Specificity = 0.2 Frequency = 1 Positive Predictive Value = 0.9691 Negative Predictive Value = 0.3158 Probability Level = 0.8675 Model = Model (0.8428) Sensitivity = 0.7833 1 - Specificity = 0.2 Frequency = 1 Positive Predictive Value = 0.9691 Negative Predictive Value = 0.3158 Probability Level = 0.8675 Model = Model (0.8428) Sensitivity = 0.775 1 - Specificity = 0.2 Frequency = 1 Positive Predictive Value = 0.9688 Negative Predictive Value = 0.3077 Probability Level = 0.8686 Model = Model (0.8428) Sensitivity = 0.775 1 - Specificity = 0.2 Frequency = 1 Positive Predictive Value = 0.9688 Negative Predictive Value = 0.3077 Probability Level = 0.8686 Model = Model (0.8428) Sensitivity = 0.7667 1 - Specificity = 0.2 Frequency = 2 Positive Predictive Value = 0.9684 Negative Predictive Value = 0.3 Probability Level = 0.8755 Model = Model (0.8428) Sensitivity = 0.7667 1 - Specificity = 0.2 Frequency = 2 Positive Predictive Value = 0.9684 Negative Predictive Value = 0.3 Probability Level = 0.8755 Model = Model (0.8428) Sensitivity = 0.75 1 - Specificity = 0.2 Frequency = 1 Positive Predictive Value = 0.9677 Negative Predictive Value = 0.2857 Probability Level = 0.8862 Model = Model (0.8428) Sensitivity = 0.75 1 - Specificity = 0.2 Frequency = 1 Positive Predictive Value = 0.9677 Negative Predictive Value = 0.2857 Probability Level = 0.8862 Model = Model (0.8428) Sensitivity = 0.75 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9783 Negative Predictive Value = 0.3023 Probability Level = 0.8881 Model = Model (0.8428) Sensitivity = 0.75 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9783 Negative Predictive Value = 0.3023 Probability Level = 0.8881 Model = Model (0.8428) Sensitivity = 0.7417 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.978 Negative Predictive Value = 0.2955 Probability Level = 0.8934 Model = Model (0.8428) Sensitivity = 0.7417 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.978 Negative Predictive Value = 0.2955 Probability Level = 0.8934 Model = Model (0.8428) Sensitivity = 0.7333 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9778 Negative Predictive Value = 0.2889 Probability Level = 0.8992 Model = Model (0.8428) Sensitivity = 0.7333 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9778 Negative Predictive Value = 0.2889 Probability Level = 0.8992 Model = Model (0.8428) Sensitivity = 0.725 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9775 Negative Predictive Value = 0.2826 Probability Level = 0.9014 Model = Model (0.8428) Sensitivity = 0.725 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9775 Negative Predictive Value = 0.2826 Probability Level = 0.9014 Model = Model (0.8428) Sensitivity = 0.7167 1 - Specificity = 0.1333 Frequency = 3 Positive Predictive Value = 0.9773 Negative Predictive Value = 0.2766 Probability Level = 0.9032 Model = Model (0.8428) Sensitivity = 0.7167 1 - Specificity = 0.1333 Frequency = 3 Positive Predictive Value = 0.9773 Negative Predictive Value = 0.2766 Probability Level = 0.9032 Model = Model (0.8428) Sensitivity = 0.6917 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9765 Negative Predictive Value = 0.26 Probability Level = 0.9064 Model = Model (0.8428) Sensitivity = 0.6917 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9765 Negative Predictive Value = 0.26 Probability Level = 0.9064 Model = Model (0.8428) Sensitivity = 0.6833 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9762 Negative Predictive Value = 0.2549 Probability Level = 0.9082 Model = Model (0.8428) Sensitivity = 0.6833 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9762 Negative Predictive Value = 0.2549 Probability Level = 0.9082 Model = Model (0.8428) Sensitivity = 0.675 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9759 Negative Predictive Value = 0.25 Probability Level = 0.9123 Model = Model (0.8428) Sensitivity = 0.675 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9759 Negative Predictive Value = 0.25 Probability Level = 0.9123 Model = Model (0.8428) Sensitivity = 0.6667 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9756 Negative Predictive Value = 0.2453 Probability Level = 0.9147 Model = Model (0.8428) Sensitivity = 0.6667 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9756 Negative Predictive Value = 0.2453 Probability Level = 0.9147 Model = Model (0.8428) Sensitivity = 0.6583 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9753 Negative Predictive Value = 0.2407 Probability Level = 0.9201 Model = Model (0.8428) Sensitivity = 0.6583 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9753 Negative Predictive Value = 0.2407 Probability Level = 0.9201 Model = Model (0.8428) Sensitivity = 0.65 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.975 Negative Predictive Value = 0.2364 Probability Level = 0.926 Model = Model (0.8428) Sensitivity = 0.65 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.975 Negative Predictive Value = 0.2364 Probability Level = 0.926 Model = Model (0.8428) Sensitivity = 0.6417 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9747 Negative Predictive Value = 0.2321 Probability Level = 0.9297 Model = Model (0.8428) Sensitivity = 0.6417 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9747 Negative Predictive Value = 0.2321 Probability Level = 0.9297 Model = Model (0.8428) Sensitivity = 0.6333 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9744 Negative Predictive Value = 0.2281 Probability Level = 0.9315 Model = Model (0.8428) Sensitivity = 0.6333 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9744 Negative Predictive Value = 0.2281 Probability Level = 0.9315 Model = Model (0.8428) Sensitivity = 0.625 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.974 Negative Predictive Value = 0.2241 Probability Level = 0.9349 Model = Model (0.8428) Sensitivity = 0.625 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.974 Negative Predictive Value = 0.2241 Probability Level = 0.9349 Model = Model (0.8428) Sensitivity = 0.6167 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9737 Negative Predictive Value = 0.2203 Probability Level = 0.9422 Model = Model (0.8428) Sensitivity = 0.6167 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9737 Negative Predictive Value = 0.2203 Probability Level = 0.9422 Model = Model (0.8428) Sensitivity = 0.6083 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9733 Negative Predictive Value = 0.2167 Probability Level = 0.9443 Model = Model (0.8428) Sensitivity = 0.6083 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9733 Negative Predictive Value = 0.2167 Probability Level = 0.9443 Model = Model (0.8428) Sensitivity = 0.6 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.973 Negative Predictive Value = 0.2131 Probability Level = 0.9446 Model = Model (0.8428) Sensitivity = 0.6 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.973 Negative Predictive Value = 0.2131 Probability Level = 0.9446 Model = Model (0.8428) Sensitivity = 0.5917 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9726 Negative Predictive Value = 0.2097 Probability Level = 0.9457 Model = Model (0.8428) Sensitivity = 0.5917 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9726 Negative Predictive Value = 0.2097 Probability Level = 0.9457 Model = Model (0.8428) Sensitivity = 0.5833 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9722 Negative Predictive Value = 0.2063 Probability Level = 0.9491 Model = Model (0.8428) Sensitivity = 0.5833 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9722 Negative Predictive Value = 0.2063 Probability Level = 0.9491 Model = Model (0.8428) Sensitivity = 0.575 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9718 Negative Predictive Value = 0.2031 Probability Level = 0.9497 Model = Model (0.8428) Sensitivity = 0.575 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9718 Negative Predictive Value = 0.2031 Probability Level = 0.9497 Model = Model (0.8428) Sensitivity = 0.5667 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9714 Negative Predictive Value = 0.2 Probability Level = 0.9506 Model = Model (0.8428) Sensitivity = 0.5667 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9714 Negative Predictive Value = 0.2 Probability Level = 0.9506 Model = Model (0.8428) Sensitivity = 0.5583 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.971 Negative Predictive Value = 0.197 Probability Level = 0.951 Model = Model (0.8428) Sensitivity = 0.5583 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.971 Negative Predictive Value = 0.197 Probability Level = 0.951 Model = Model (0.8428) Sensitivity = 0.55 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9706 Negative Predictive Value = 0.194 Probability Level = 0.9546 Model = Model (0.8428) Sensitivity = 0.55 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9706 Negative Predictive Value = 0.194 Probability Level = 0.9546 Model = Model (0.8428) Sensitivity = 0.5417 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9701 Negative Predictive Value = 0.1912 Probability Level = 0.9546 Model = Model (0.8428) Sensitivity = 0.5417 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9701 Negative Predictive Value = 0.1912 Probability Level = 0.9546 Model = Model (0.8428) Sensitivity = 0.5333 1 - Specificity = 0.1333 Frequency = 2 Positive Predictive Value = 0.9697 Negative Predictive Value = 0.1884 Probability Level = 0.9555 Model = Model (0.8428) Sensitivity = 0.5333 1 - Specificity = 0.1333 Frequency = 2 Positive Predictive Value = 0.9697 Negative Predictive Value = 0.1884 Probability Level = 0.9555 Model = Model (0.8428) Sensitivity = 0.5167 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9688 Negative Predictive Value = 0.1831 Probability Level = 0.9577 Model = Model (0.8428) Sensitivity = 0.5167 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9688 Negative Predictive Value = 0.1831 Probability Level = 0.9577 Model = Model (0.8428) Sensitivity = 0.5083 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9683 Negative Predictive Value = 0.1806 Probability Level = 0.9585 Model = Model (0.8428) Sensitivity = 0.5083 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9683 Negative Predictive Value = 0.1806 Probability Level = 0.9585 Model = Model (0.8428) Sensitivity = 0.5 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9677 Negative Predictive Value = 0.1781 Probability Level = 0.9598 Model = Model (0.8428) Sensitivity = 0.5 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9677 Negative Predictive Value = 0.1781 Probability Level = 0.9598 Model = Model (0.8428) Sensitivity = 0.4917 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9672 Negative Predictive Value = 0.1757 Probability Level = 0.9602 Model = Model (0.8428) Sensitivity = 0.4917 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9672 Negative Predictive Value = 0.1757 Probability Level = 0.9602 Model = Model (0.8428) Sensitivity = 0.4833 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9667 Negative Predictive Value = 0.1733 Probability Level = 0.9619 Model = Model (0.8428) Sensitivity = 0.4833 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9667 Negative Predictive Value = 0.1733 Probability Level = 0.9619 Model = Model (0.8428) Sensitivity = 0.475 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9661 Negative Predictive Value = 0.1711 Probability Level = 0.9626 Model = Model (0.8428) Sensitivity = 0.475 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9661 Negative Predictive Value = 0.1711 Probability Level = 0.9626 Model = Model (0.8428) Sensitivity = 0.4667 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9655 Negative Predictive Value = 0.1688 Probability Level = 0.9627 Model = Model (0.8428) Sensitivity = 0.4667 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9655 Negative Predictive Value = 0.1688 Probability Level = 0.9627 Model = Model (0.8428) Sensitivity = 0.4583 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9649 Negative Predictive Value = 0.1667 Probability Level = 0.9628 Model = Model (0.8428) Sensitivity = 0.4583 1 - Specificity = 0.1333 Frequency = 1 Positive Predictive Value = 0.9649 Negative Predictive Value = 0.1667 Probability Level = 0.9628 Model = Model (0.8428) Sensitivity = 0.4583 1 - Specificity = 0.0667 Frequency = 1 Positive Predictive Value = 0.9821 Negative Predictive Value = 0.1772 Probability Level = 0.9634 Model = Model (0.8428) Sensitivity = 0.4583 1 - Specificity = 0.0667 Frequency = 1 Positive Predictive Value = 0.9821 Negative Predictive Value = 0.1772 Probability Level = 0.9634 Model = Model (0.8428) Sensitivity = 0.45 1 - Specificity = 0.0667 Frequency = 1 Positive Predictive Value = 0.9818 Negative Predictive Value = 0.175 Probability Level = 0.9638 Model = Model (0.8428) Sensitivity = 0.45 1 - Specificity = 0.0667 Frequency = 1 Positive Predictive Value = 0.9818 Negative Predictive Value = 0.175 Probability Level = 0.9638 Model = Model (0.8428) Sensitivity = 0.4417 1 - Specificity = 0.0667 Frequency = 1 Positive Predictive Value = 0.9815 Negative Predictive Value = 0.1728 Probability Level = 0.965 Model = Model (0.8428) Sensitivity = 0.4417 1 - Specificity = 0.0667 Frequency = 1 Positive Predictive Value = 0.9815 Negative Predictive Value = 0.1728 Probability Level = 0.965 Model = Model (0.8428) Sensitivity = 0.4417 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1829 Probability Level = 0.9671 Model = Model (0.8428) Sensitivity = 0.4417 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1829 Probability Level = 0.9671 Model = Model (0.8428) Sensitivity = 0.4333 1 - Specificity = 0 Frequency = 2 Positive Predictive Value = 1 Negative Predictive Value = 0.1807 Probability Level = 0.9688 Model = Model (0.8428) Sensitivity = 0.4333 1 - Specificity = 0 Frequency = 2 Positive Predictive Value = 1 Negative Predictive Value = 0.1807 Probability Level = 0.9688 Model = Model (0.8428) Sensitivity = 0.4167 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1765 Probability Level = 0.9699 Model = Model (0.8428) Sensitivity = 0.4167 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1765 Probability Level = 0.9699 Model = Model (0.8428) Sensitivity = 0.4083 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1744 Probability Level = 0.9707 Model = Model (0.8428) Sensitivity = 0.4083 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1744 Probability Level = 0.9707 Model = Model (0.8428) Sensitivity = 0.4 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1724 Probability Level = 0.9735 Model = Model (0.8428) Sensitivity = 0.4 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1724 Probability Level = 0.9735 Model = Model (0.8428) Sensitivity = 0.3917 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1705 Probability Level = 0.9736 Model = Model (0.8428) Sensitivity = 0.3917 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1705 Probability Level = 0.9736 Model = Model (0.8428) Sensitivity = 0.3833 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1685 Probability Level = 0.9786 Model = Model (0.8428) Sensitivity = 0.3833 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1685 Probability Level = 0.9786 Model = Model (0.8428) Sensitivity = 0.375 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1667 Probability Level = 0.979 Model = Model (0.8428) Sensitivity = 0.375 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1667 Probability Level = 0.979 Model = Model (0.8428) Sensitivity = 0.3667 1 - Specificity = 0 Frequency = 2 Positive Predictive Value = 1 Negative Predictive Value = 0.1648 Probability Level = 0.9795 Model = Model (0.8428) Sensitivity = 0.3667 1 - Specificity = 0 Frequency = 2 Positive Predictive Value = 1 Negative Predictive Value = 0.1648 Probability Level = 0.9795 Model = Model (0.8428) Sensitivity = 0.35 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1613 Probability Level = 0.9797 Model = Model (0.8428) Sensitivity = 0.35 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1613 Probability Level = 0.9797 Model = Model (0.8428) Sensitivity = 0.3417 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1596 Probability Level = 0.9821 Model = Model (0.8428) Sensitivity = 0.3417 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1596 Probability Level = 0.9821 Model = Model (0.8428) Sensitivity = 0.3333 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1579 Probability Level = 0.9826 Model = Model (0.8428) Sensitivity = 0.3333 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1579 Probability Level = 0.9826 Model = Model (0.8428) Sensitivity = 0.325 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1563 Probability Level = 0.9831 Model = Model (0.8428) Sensitivity = 0.325 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1563 Probability Level = 0.9831 Model = Model (0.8428) Sensitivity = 0.3167 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1546 Probability Level = 0.9835 Model = Model (0.8428) Sensitivity = 0.3167 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1546 Probability Level = 0.9835 Model = Model (0.8428) Sensitivity = 0.3083 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1531 Probability Level = 0.9836 Model = Model (0.8428) Sensitivity = 0.3083 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1531 Probability Level = 0.9836 Model = Model (0.8428) Sensitivity = 0.3 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1515 Probability Level = 0.9843 Model = Model (0.8428) Sensitivity = 0.3 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1515 Probability Level = 0.9843 Model = Model (0.8428) Sensitivity = 0.2917 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.15 Probability Level = 0.9848 Model = Model (0.8428) Sensitivity = 0.2917 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.15 Probability Level = 0.9848 Model = Model (0.8428) Sensitivity = 0.2833 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1485 Probability Level = 0.9855 Model = Model (0.8428) Sensitivity = 0.2833 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1485 Probability Level = 0.9855 Model = Model (0.8428) Sensitivity = 0.275 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1471 Probability Level = 0.9856 Model = Model (0.8428) Sensitivity = 0.275 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1471 Probability Level = 0.9856 Model = Model (0.8428) Sensitivity = 0.2667 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1456 Probability Level = 0.9862 Model = Model (0.8428) Sensitivity = 0.2667 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1456 Probability Level = 0.9862 Model = Model (0.8428) Sensitivity = 0.2583 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1442 Probability Level = 0.9866 Model = Model (0.8428) Sensitivity = 0.2583 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1442 Probability Level = 0.9866 Model = Model (0.8428) Sensitivity = 0.25 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1429 Probability Level = 0.9871 Model = Model (0.8428) Sensitivity = 0.25 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1429 Probability Level = 0.9871 Model = Model (0.8428) Sensitivity = 0.2417 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1415 Probability Level = 0.9875 Model = Model (0.8428) Sensitivity = 0.2417 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1415 Probability Level = 0.9875 Model = Model (0.8428) Sensitivity = 0.2333 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1402 Probability Level = 0.9897 Model = Model (0.8428) Sensitivity = 0.2333 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1402 Probability Level = 0.9897 Model = Model (0.8428) Sensitivity = 0.225 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1389 Probability Level = 0.9898 Model = Model (0.8428) Sensitivity = 0.225 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1389 Probability Level = 0.9898 Model = Model (0.8428) Sensitivity = 0.2167 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1376 Probability Level = 0.9912 Model = Model (0.8428) Sensitivity = 0.2167 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1376 Probability Level = 0.9912 Model = Model (0.8428) Sensitivity = 0.2083 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1364 Probability Level = 0.9912 Model = Model (0.8428) Sensitivity = 0.2083 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1364 Probability Level = 0.9912 Model = Model (0.8428) Sensitivity = 0.2 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1351 Probability Level = 0.9921 Model = Model (0.8428) Sensitivity = 0.2 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1351 Probability Level = 0.9921 Model = Model (0.8428) Sensitivity = 0.1917 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1339 Probability Level = 0.9927 Model = Model (0.8428) Sensitivity = 0.1917 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1339 Probability Level = 0.9927 Model = Model (0.8428) Sensitivity = 0.1833 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1327 Probability Level = 0.9928 Model = Model (0.8428) Sensitivity = 0.1833 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1327 Probability Level = 0.9928 Model = Model (0.8428) Sensitivity = 0.175 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1316 Probability Level = 0.9928 Model = Model (0.8428) Sensitivity = 0.175 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1316 Probability Level = 0.9928 Model = Model (0.8428) Sensitivity = 0.1667 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1304 Probability Level = 0.9936 Model = Model (0.8428) Sensitivity = 0.1667 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1304 Probability Level = 0.9936 Model = Model (0.8428) Sensitivity = 0.1583 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1293 Probability Level = 0.994 Model = Model (0.8428) Sensitivity = 0.1583 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1293 Probability Level = 0.994 Model = Model (0.8428) Sensitivity = 0.15 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1282 Probability Level = 0.9946 Model = Model (0.8428) Sensitivity = 0.15 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1282 Probability Level = 0.9946 Model = Model (0.8428) Sensitivity = 0.1417 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1271 Probability Level = 0.9948 Model = Model (0.8428) Sensitivity = 0.1417 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1271 Probability Level = 0.9948 Model = Model (0.8428) Sensitivity = 0.1333 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1261 Probability Level = 0.9954 Model = Model (0.8428) Sensitivity = 0.1333 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1261 Probability Level = 0.9954 Model = Model (0.8428) Sensitivity = 0.125 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.125 Probability Level = 0.9961 Model = Model (0.8428) Sensitivity = 0.125 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.125 Probability Level = 0.9961 Model = Model (0.8428) Sensitivity = 0.1167 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.124 Probability Level = 0.9968 Model = Model (0.8428) Sensitivity = 0.1167 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.124 Probability Level = 0.9968 Model = Model (0.8428) Sensitivity = 0.1083 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.123 Probability Level = 0.9968 Model = Model (0.8428) Sensitivity = 0.1083 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.123 Probability Level = 0.9968 Model = Model (0.8428) Sensitivity = 0.1 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.122 Probability Level = 0.997 Model = Model (0.8428) Sensitivity = 0.1 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.122 Probability Level = 0.997 Model = Model (0.8428) Sensitivity = 0.0917 1 - Specificity = 0 Frequency = 2 Positive Predictive Value = 1 Negative Predictive Value = 0.121 Probability Level = 0.9972 Model = Model (0.8428) Sensitivity = 0.0917 1 - Specificity = 0 Frequency = 2 Positive Predictive Value = 1 Negative Predictive Value = 0.121 Probability Level = 0.9972 Model = Model (0.8428) Sensitivity = 0.075 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.119 Probability Level = 0.9977 Model = Model (0.8428) Sensitivity = 0.075 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.119 Probability Level = 0.9977 Model = Model (0.8428) Sensitivity = 0.0667 1 - Specificity = 0 Frequency = 2 Positive Predictive Value = 1 Negative Predictive Value = 0.1181 Probability Level = 0.998 Model = Model (0.8428) Sensitivity = 0.0667 1 - Specificity = 0 Frequency = 2 Positive Predictive Value = 1 Negative Predictive Value = 0.1181 Probability Level = 0.998 Model = Model (0.8428) Sensitivity = 0.05 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1163 Probability Level = 0.9987 Model = Model (0.8428) Sensitivity = 0.05 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1163 Probability Level = 0.9987 Model = Model (0.8428) Sensitivity = 0.0417 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1154 Probability Level = 0.9989 Model = Model (0.8428) Sensitivity = 0.0417 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1154 Probability Level = 0.9989 Model = Model (0.8428) Sensitivity = 0.0333 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1145 Probability Level = 0.9989 Model = Model (0.8428) Sensitivity = 0.0333 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1145 Probability Level = 0.9989 Model = Model (0.8428) Sensitivity = 0.025 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1136 Probability Level = 0.9991 Model = Model (0.8428) Sensitivity = 0.025 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1136 Probability Level = 0.9991 Model = Model (0.8428) Sensitivity = 0.0167 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1128 Probability Level = 0.9994 Model = Model (0.8428) Sensitivity = 0.0167 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1128 Probability Level = 0.9994 Model = Model (0.8428) Sensitivity = 0.0083 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1119 Probability Level = 0.9997 Model = Model (0.8428) Sensitivity = 0.0083 1 - Specificity = 0 Frequency = 1 Positive Predictive Value = 1 Negative Predictive Value = 0.1119 Probability Level = 0.9997 Model = Model (0.8428) Sensitivity = 0 1 - Specificity = 0 Frequency = 0 Positive Predictive Value = . Negative Predictive Value = 8 Probability Level = 1 Slope = 1 Y = 0
ROC Curve for Model

Influence Plots

Pearson Residuals

Pearson Residual = 0.0734 Case Number = 135 Price = 1 Pearson Residual = 0.0852 Case Number = 134 Price = 1 Pearson Residual = 0.1439 Case Number = 133 Price = 1 Pearson Residual = 0.1971 Case Number = 132 Price = 1 Pearson Residual = 0.2271 Case Number = 131 Price = 1 Pearson Residual = -0.517 Case Number = 130 Price = 0 Pearson Residual = 0.2046 Case Number = 129 Price = 1 Pearson Residual = 0.1649 Case Number = 128 Price = 1 Pearson Residual = -2.016 Case Number = 127 Price = 0 Pearson Residual = 0.4683 Case Number = 126 Price = 1 Pearson Residual = 0.7516 Case Number = 125 Price = 1 Pearson Residual = 0.4688 Case Number = 124 Price = 1 Pearson Residual = 0.0528 Case Number = 123 Price = 1 Pearson Residual = 0.045 Case Number = 122 Price = 1 Pearson Residual = 0.3909 Case Number = 121 Price = 1 Pearson Residual = 0.697 Case Number = 120 Price = 1 Pearson Residual = 0.1313 Case Number = 119 Price = 1 Pearson Residual = 0.1349 Case Number = 118 Price = 1 Pearson Residual = 0.1466 Case Number = 117 Price = 1 Pearson Residual = 0.0528 Case Number = 116 Price = 1 Pearson Residual = 0.0778 Case Number = 115 Price = 1 Pearson Residual = 0.2826 Case Number = 114 Price = 1 Pearson Residual = -2.046 Case Number = 113 Price = 0 Pearson Residual = 0.0943 Case Number = 112 Price = 1 Pearson Residual = 0.1125 Case Number = 111 Price = 1 Pearson Residual = 0.2302 Case Number = 110 Price = 1 Pearson Residual = 0.4732 Case Number = 109 Price = 1 Pearson Residual = 0.4683 Case Number = 108 Price = 1 Pearson Residual = 0.1166 Case Number = 107 Price = 1 Pearson Residual = 0.389 Case Number = 106 Price = 1 Pearson Residual = 0.1017 Case Number = 105 Price = 1 Pearson Residual = 0.0721 Case Number = 104 Price = 1 Pearson Residual = 0.275 Case Number = 103 Price = 1 Pearson Residual = 1.1215 Case Number = 102 Price = 1 Pearson Residual = 0.2639 Case Number = 101 Price = 1 Pearson Residual = 0.1211 Case Number = 100 Price = 1 Pearson Residual = 0.045 Case Number = 99 Price = 1 Pearson Residual = 0.1762 Case Number = 98 Price = 1 Pearson Residual = 0.1794 Case Number = 97 Price = 1 Pearson Residual = 0.3307 Case Number = 96 Price = 1 Pearson Residual = 0.1645 Case Number = 95 Price = 1 Pearson Residual = -2.019 Case Number = 94 Price = 0 Pearson Residual = 0.1446 Case Number = 93 Price = 1 Pearson Residual = 0.9999 Case Number = 92 Price = 1 Pearson Residual = -2.424 Case Number = 91 Price = 0 Pearson Residual = 0.0805 Case Number = 90 Price = 1 Pearson Residual = -1.166 Case Number = 89 Price = 0 Pearson Residual = 0.0894 Case Number = 88 Price = 1 Pearson Residual = 0.208 Case Number = 87 Price = 1 Pearson Residual = 0.1446 Case Number = 86 Price = 1 Pearson Residual = -0.665 Case Number = 85 Price = 0 Pearson Residual = 0.5145 Case Number = 84 Price = 1 Pearson Residual = 0.482 Case Number = 83 Price = 1 Pearson Residual = 0.0622 Case Number = 82 Price = 1 Pearson Residual = 0.446 Case Number = 81 Price = 1 Pearson Residual = 0.2317 Case Number = 80 Price = 1 Pearson Residual = 0.228 Case Number = 79 Price = 1 Pearson Residual = 0.4343 Case Number = 78 Price = 1 Pearson Residual = 0.3273 Case Number = 77 Price = 1 Pearson Residual = -5.088 Case Number = 76 Price = 0 Pearson Residual = -2.19 Case Number = 75 Price = 0 Pearson Residual = -0.378 Case Number = 74 Price = 0 Pearson Residual = 0.3771 Case Number = 73 Price = 1 Pearson Residual = 0.4954 Case Number = 72 Price = 1 Pearson Residual = 0.1479 Case Number = 71 Price = 1 Pearson Residual = 0.318 Case Number = 70 Price = 1 Pearson Residual = 0.3454 Case Number = 69 Price = 1 Pearson Residual = 0.6398 Case Number = 68 Price = 1 Pearson Residual = 0.7708 Case Number = 67 Price = 1 Pearson Residual = -1.072 Case Number = 66 Price = 0 Pearson Residual = 0.2713 Case Number = 65 Price = 1 Pearson Residual = 0.3055 Case Number = 64 Price = 1 Pearson Residual = 0.4285 Case Number = 63 Price = 1 Pearson Residual = 0.5234 Case Number = 62 Price = 1 Pearson Residual = 0.0241 Case Number = 61 Price = 1 Pearson Residual = 0.2037 Case Number = 60 Price = 1 Pearson Residual = 0.0307 Case Number = 59 Price = 1 Pearson Residual = 0.5409 Case Number = 58 Price = 1 Pearson Residual = 0.1265 Case Number = 57 Price = 1 Pearson Residual = 0.1292 Case Number = 56 Price = 1 Pearson Residual = 0.1949 Case Number = 55 Price = 1 Pearson Residual = 0.3349 Case Number = 54 Price = 1 Pearson Residual = -5.253 Case Number = 53 Price = 0 Pearson Residual = 0.6201 Case Number = 52 Price = 1 Pearson Residual = -2.538 Case Number = 51 Price = 0 Pearson Residual = 0.0944 Case Number = 50 Price = 1 Pearson Residual = 0.3273 Case Number = 49 Price = 1 Pearson Residual = 0.446 Case Number = 48 Price = 1 Pearson Residual = 0.1844 Case Number = 47 Price = 1 Pearson Residual = 0.1736 Case Number = 46 Price = 1 Pearson Residual = 0.0565 Case Number = 45 Price = 1 Pearson Residual = 0.017 Case Number = 44 Price = 1 Pearson Residual = 0.0361 Case Number = 43 Price = 1 Pearson Residual = 0.1794 Case Number = 42 Price = 1 Pearson Residual = 0.3771 Case Number = 41 Price = 1 Pearson Residual = 0.3101 Case Number = 40 Price = 1 Pearson Residual = 0.2429 Case Number = 39 Price = 1 Pearson Residual = 0.0548 Case Number = 38 Price = 1 Pearson Residual = 0.8017 Case Number = 37 Price = 1 Pearson Residual = 0.1184 Case Number = 36 Price = 1 Pearson Residual = 0.7304 Case Number = 35 Price = 1 Pearson Residual = 0.3214 Case Number = 34 Price = 1 Pearson Residual = 0.1991 Case Number = 33 Price = 1 Pearson Residual = 0.2476 Case Number = 32 Price = 1 Pearson Residual = 0.5899 Case Number = 31 Price = 1 Pearson Residual = 0.2396 Case Number = 30 Price = 1 Pearson Residual = 0.5767 Case Number = 29 Price = 1 Pearson Residual = 0.3933 Case Number = 28 Price = 1 Pearson Residual = 0.0565 Case Number = 27 Price = 1 Pearson Residual = 0.0678 Case Number = 26 Price = 1 Pearson Residual = 0.1213 Case Number = 25 Price = 1 Pearson Residual = 0.2421 Case Number = 24 Price = 1 Pearson Residual = 0.3273 Case Number = 23 Price = 1 Pearson Residual = 0.1331 Case Number = 22 Price = 1 Pearson Residual = 0.355 Case Number = 21 Price = 1 Pearson Residual = 0.2947 Case Number = 20 Price = 1 Pearson Residual = 0.2181 Case Number = 19 Price = 1 Pearson Residual = 0.0857 Case Number = 18 Price = 1 Pearson Residual = 0.0334 Case Number = 17 Price = 1 Pearson Residual = 0.4343 Case Number = 16 Price = 1 Pearson Residual = 0.1297 Case Number = 15 Price = 1 Pearson Residual = 0.1939 Case Number = 14 Price = 1 Pearson Residual = 0.0854 Case Number = 13 Price = 1 Pearson Residual = 0.2159 Case Number = 12 Price = 1 Pearson Residual = -2.791 Case Number = 11 Price = 0 Pearson Residual = 0.102 Case Number = 10 Price = 1 Pearson Residual = 0.2101 Case Number = 9 Price = 1 Pearson Residual = 0.2182 Case Number = 8 Price = 1 Pearson Residual = 0.1969 Case Number = 7 Price = 1 Pearson Residual = 0.048 Case Number = 6 Price = 1 Pearson Residual = 0.2159 Case Number = 5 Price = 1 Pearson Residual = -1.297 Case Number = 4 Price = 0 Pearson Residual = 0.1145 Case Number = 3 Price = 1 Pearson Residual = 0.1244 Case Number = 2 Price = 1 Pearson Residual = 0.0331 Case Number = 1 Price = 1 Y = 0
Plot of Pearson Chi-Square Residuals by Case Number.

Deviance Residuals

Deviance Residual = 0.1036 Case Number = 135 Price = 1 Deviance Residual = 0.1203 Case Number = 134 Price = 1 Deviance Residual = 0.2025 Case Number = 133 Price = 1 Deviance Residual = 0.276 Case Number = 132 Price = 1 Deviance Residual = 0.3171 Case Number = 131 Price = 1 Deviance Residual = -0.688 Case Number = 130 Price = 0 Deviance Residual = 0.2864 Case Number = 129 Price = 1 Deviance Residual = 0.2317 Case Number = 128 Price = 1 Deviance Residual = -1.801 Case Number = 127 Price = 0 Deviance Residual = 0.6297 Case Number = 126 Price = 1 Deviance Residual = 0.9464 Case Number = 125 Price = 1 Deviance Residual = 0.6304 Case Number = 124 Price = 1 Deviance Residual = 0.0746 Case Number = 123 Price = 1 Deviance Residual = 0.0636 Case Number = 122 Price = 1 Deviance Residual = 0.5333 Case Number = 121 Price = 1 Deviance Residual = 0.8899 Case Number = 120 Price = 1 Deviance Residual = 0.1849 Case Number = 119 Price = 1 Deviance Residual = 0.19 Case Number = 118 Price = 1 Deviance Residual = 0.2062 Case Number = 117 Price = 1