MedicalStat

Total
Total N
Decimals:

## Results

 Per:

Disease Prevalence Interpretation Value SE % Confidence Interval
Null Hypothesis Z value P value
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. $$DOR = \frac{LR+}{LR-}$$
F1 Score Interpretation Value
The F1-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. $$Power = 1 - \beta = sensitivity$$