Diagnostic Test 2×2 Table Calculator
Enter the 2×2 table's true positives, false positives, false negatives and true negatives to compute sensitivity, specificity, positive/negative predictive values, accuracy, likelihood ratios, the diagnostic odds ratio and Youden's index; proportions include Wilson 95% confidence intervals.
① Fill in the 2×2 table
| Gold standard + | Gold standard − | |
|---|---|---|
| Test + | ||
| Test − |
How to use & methodology
What do the 2×2 metrics mean?
Sensitivity = TP/(TP+FN), reflecting few missed cases; specificity = TN/(TN+FP), reflecting few false alarms; PPV is the proportion of test-positives who are truly diseased; NPV is the proportion of test-negatives who are truly non-diseased.
Why do predictive values change?
PPV and NPV depend on the population prevalence: for the same test, PPV is higher in a high-prevalence population and lower in a low-prevalence one. When citing literature predictive values, check whether their prevalence matches your population; likelihood ratios are unaffected by prevalence and more stable.
How do I read likelihood ratios?
The larger the positive LR (+LR), the more a positive test indicates disease; above 10 is usually strong diagnostic value. The smaller the negative LR (−LR), the better a negative test rules disease out; below 0.1 is strong. The diagnostic odds ratio (DOR) summarizes overall discrimination.
Why the Wilson method for CIs?
For proportions, the traditional Wald interval is distorted at small samples or when the proportion is near 0/1. The Wilson method is more robust at small samples and never goes out of bounds, so sensitivity, specificity and other proportions here use Wilson 95% CIs.