Calculates the probability of having a condition after receiving a diagnostic test result (using Bayes' Theorem).
Start with your values, or try a preset.
Enter Pre-test Probability (%), Sensitivity (%), and Specificity (%) in the units shown.
Read Specificity (Decimal), Sensitivity (Decimal), Pre-test Probability (Decimal), Positive Likelihood Ratio, Post-test Odds, and Post-test Probability (%) in the results panel. Results update as you change the inputs.
Choose a preset to load an example, then adjust the values for your situation.
See the inputs and their calculated results.
Pre-test Probability (%): 10 %; Sensitivity (%): 95 %; Specificity (%): 95 %
Specificity (Decimal): 0.95; Sensitivity (Decimal): 0.95; Pre-test Probability (Decimal): 0.1; Positive Likelihood Ratio: 19; Post-test Odds: 2.111111111; Post-test Probability (%): 67.85714286 %
Pre-test Probability (%): 20 %; Sensitivity (%): 80 %; Specificity (%): 80 %
Specificity (Decimal): 0.8; Sensitivity (Decimal): 0.8; Pre-test Probability (Decimal): 0.2; Positive Likelihood Ratio: 4; Post-test Odds: 1; Post-test Probability (%): 50 %
Pre-test Probability (%): 5 %; Sensitivity (%): 90 %; Specificity (%): 90 %
Specificity (Decimal): 0.9; Sensitivity (Decimal): 0.9; Pre-test Probability (Decimal): 0.05; Positive Likelihood Ratio: 9; Post-test Odds: 0.4736842105; Post-test Probability (%): 32.14285714 %
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