Table 5.
Logistic regression model predictive analysis.
| Number of variables | 19 | 13 | 11 |
|---|---|---|---|
| Sensitive (%) | 2% | 2% | 2% |
| Specificity (%) | 99% | 99% | 99% |
| FPR (%) | 0.26% | 0.20% | 0.26% |
| FNR (%) | 97% | 97% | 97% |
| Classification accuracy (%) | 91% | 91% | 90.0% |
| AUC | 0.741 | 0.731 | 0.706 |
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