The proportion that people with the disease make out of all persons in the sample. \( DP = \frac{TP+FN}{N} \)
DP
Sensitivity
Interpretation
Value
SE
% Confidence Interval
Null Hypothesis
Z value
P value
The probability that you test positive if you have the disease. It's the same as the power (1 - β) of the test. \( Sensitivity = \frac{TP}{TP+FN} \)
Sensitivity
Specificity
Interpretation
Value
SE
% Confidence Interval
Null Hypothesis
Z value
P value
The probability that you test negative if you don't have the disease. \( Specificity = \frac{TN}{FP+TN} \)
Specificity
Positive Predictive Value
Interpretation
Value
SE
% Confidence Interval
Null Hypothesis
Z value
P value
The probability that you have the disease if you test positive. \( PPV = \frac{TP}{TP+FP} \)
PPV
Negative Predictive Value
Interpretation
Value
SE
% Confidence Interval
Null Hypothesis
Z value
P value
The probability that you don't have the disease if you test negative. \( NPV = \frac{TN}{FN+TN} \)
NPV
Accuracy
Interpretation
Value
SE
% Confidence Interval
Null Hypothesis
Z value
P value
The probability that the test gives the correct answer (either positive or negative) \( A = \frac{TP+TN}{N} \)
Accuracy
False Positive Rate
Interpretation
Value
SE
% Confidence Interval
Null Hypothesis
Z value
P value
The probability that you test positive if you don't have the disease. It's the same as the risk of type 1 error (α).
\( FPR = \frac{FP}{FP+TN} \)
FPR
False Negative Rate
Interpretation
Value
SE
% Confidence Interval
Null Hypothesis
Z value
P value
The "miss rate". The probability that you test negative if you have the disease. It's the same as the risk of type 2 error (β).
\( FNR = \frac{FN}{TP+FN} \)
FNR
False Discovery Rate
Interpretation
Value
SE
% Confidence Interval
Null Hypothesis
Z value
P value
The probability that you don't have the disease if you test positive. \( FDR = \frac{FP}{TP+FP} \)
FDR
False Omission Rate
Interpretation
Value
SE
% Confidence Interval
Null Hypothesis
Z value
P value
The probability that you have the disease if you test negative. \( FOR = \frac{FN}{FN+TN} \)
FOR
Positive Likelihood Rate
Interpretation
Value
The probability that a person with the disease tests positive divided by the probability that a person without the disease
tests positive. If the rate is greater than 1 the test is more likely to give a true positive than a false positive. If the
rate is between 0 and 1 the test is more likely to give a false positive than a true positive. \( LR+ = \frac{sensitivity}{1 - specificity} \)
Negative Likelihood Ratio
Interpretation
Value
The probability that a person with the disease tests negative divided by the probability that a person without the disease
tests negative. If the rate is greater than 1 the test is more likely to give a false negative than a true negative. If the
rate is between 0 and 1 the test is more likely to give a true negative than a false negative. \( LR- = \frac{1 - sensitivity}{specificity} \)
Diagnostic Odds Ratio
Interpretation
Value
The rate between the odds of a person testing positive who has the disease relative to the odds of a person testing positive who do
not have the disease. \( DOR = \frac{LR+}{LR-} \)
F_{1} Score
Interpretation
Value
The F_{1}-score can be used as a single measure of performance of the test for the positive class.
It is a measure of the test's accuracy. $$ F_1 = 2 \times \frac{PPV \times Sensitivity}{PPV + Sensitivity} $$
Power
Interpretation
Value
The power of the test is the probability that you test positive if you have the disease. It's the same as the sensitivity.
\( Power = 1 - \beta = sensitivity \)