Table 4.
Coefficients and Classification Indices for the Original and Replicated Logistic Regression Models
| Measure | B | SE | Wald | p | TN | FN | TP | FP | Hit rate | Sensitivity | Specificity | AUC | SE |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Model 1: Original Model (n = 206) | 151 | 3 | 17 | 30 | 83.6 | 90.0 | 82.9 | 0.913 | 0.032 | ||||
| WIF_N Screen | −0.210 | 0.180 | 1.369 | 0.244 | |||||||||
| RDN | −0.221 | 0.146 | 2.280 | 0.131 | |||||||||
| Sound Matching | −0.567 | 0.199 | 8.123 | 0.004 | |||||||||
| Oral Vocabulary | −0.010 | 0.025 | 0.160 | 0.690 | |||||||||
| WIF_N Level | 0.017 | 0.192 | 0.008 | 0.930 | |||||||||
| WIF_N Slope | −0.501 | 0.852 | 0.348 | 0.557 | |||||||||
| Constant | 7.033 | 2.534 | 7.728 | 0.006 | |||||||||
| Model 2: Replication (n = 355) | 253 | 5 | 49 | 48 | 84.8 | 90.7 | 84.0 | 0.925 | 0.015 | ||||
| WIF_N Screen | −0.210 | ||||||||||||
| RDN | −0.221 | ||||||||||||
| Sound Matching | −0.567 | ||||||||||||
| Oral Vocabulary | −0.010 | ||||||||||||
| WIF_N Level | 0.017 | ||||||||||||
| WIF_N Slope | −0.501 | ||||||||||||
| Constant | 7.033 | ||||||||||||
Note. Hit rate, sensitivity, and specificity are expressed as percentages. WIF_N Screen = Word Identification Fluency screening measure. WIF_N Level = Level of Word Identification Fluency_Narrow at week 5; WIF_N Slope = Slope of Word Identification Fluency_Narrow over 5 weeks; TN = true negatives; FN = false negatives; TP = true positives; FP = false positives; Hit rate = (TP + TN)/N; sensitivity = TP/(TP + FN); specificity = TN/(TN + FP); AUC = area under the curve; SE = standard error of AUC.