Key summaries
Open Access

Table 5

Measuring sensitivity, specificity, and Cohen’s Kappa statistic (k-Cohen).

Nets Positive (retreat case) Negative (non-retreat case)
Net 1 True: 52 True: 1651
False: 18 False: 657
Total: 70 Total: 2308
Sensitivity: 52/70 = 0.7466 Specificity: 1651/2308 = 0.7154
k-Cohen: 0.7158
Net 2 True: 50 True: 1509
False: 20 False: 799
Total: 70 Total: 2308
Sensitivity: 50/70 = 0.7143 Specificity: 1509/2308 = 0.6538
k-Cohen: 0.6552
Net 3 True: 46 True: 1598
False: 24 False: 710
Total: 70 Total: 2308
Sensitivity: 46/70 = 0.6571 Specificity: 1598/2308 = 0.6924
k-Cohen: 0.6910
Net 4 True: 49 True: 1704
False: 21 False: 604
Total: 70 Total: 2308
Sensitivity: 49/70 = 0.7000 Specificity: 1704/2308 = 0.7385
k-Cohen: 0.7369
Net 5 True: 46 True: 1616
False: 24 False: 692
Total: 70 Total: 2308
Sensitivity: 46/70 = 0.6571 Specificity: 1616/2308 = 0.7002
k-Cohen: 0.6985
Net 6 True: 48 True: 1620
False: 22 False: 688
Total: 70 Total: 2308
Sensitivity: 48/70 = 0.6857 Specificity: 1620/2308 = 0.7019
k-Cohen: 0.7011
Net 7 True: 45 True: 1669
False: 25 False: 639
Total: 70 Total: 2308
Sensitivity: 45/70 = 0.6429 Specificity: 1669/2308 = 0.7231
k-Cohen: 0.7204
Net 8 True: 49 True: 1598
False: 21 False: 710
Total: 70 Total: 2308
Sensitivity: 49/70 = 0.7000 Specificity: 1598/2308 = 0.7018
k-Cohen: 0.6922