Specificity (True Negative Rate)
Definition
The proportion of true non-matches correctly identified as non-matches. Specificity = TN / (TN + FP) = 1 minus FPR. A method with high specificity rarely produces a false alarm.
- Field
- Forensic statistics, validation
- Formula
- Specificity = TN / (TN + FP)
- Relation to FPR
- Specificity = 1 minus false positive rate
- High specificity means
- Rarely produces a false alarm
Common questions
How does specificity differ from sensitivity in a forensic method?+
Sensitivity measures how well a method catches true matches, while specificity measures how well it correctly clears true non-matches, and a method can be strong on one measure while weaker on the other.
Why does specificity alone not fully describe a method's reliability?+
A method can have high specificity yet still miss many true matches if its sensitivity is low, so validation reports pair specificity with sensitivity rather than citing either figure in isolation.
Related terms
- Decision Threshold
- The cut-off score above which a classification method declares a positive result. Raising the threshold reduces FPR but increases FNR; lowering it...
- False Negative Rate (FNR)
- The proportion of true matches (or true positives) that a classification method fails to detect, declaring them as non-matches. Also called the...
- False Positive Rate (FPR)
- The proportion of true non-matches (or true negatives) that a classification method declares as matches (or positives). Also called the type I...
- ROC Curve
- Receiver operating characteristic curve: a plot of sensitivity (y-axis) against FPR (x-axis) as the decision threshold is swept from its most lenient...
- Sensitivity (True Positive Rate)
- The proportion of true matches correctly identified as matches. Sensitivity = TP / (TP + FN) = 1 minus FNR. A method...