A neutral laboratory result card beside two probability-weight trays. Original AI-generated artwork produced for GreenCalc; not a measured diagram or empirical data display.
A negative result needs its own likelihood ratio
For a binary test, LR minus equals (1−sensitivity)/specificity. It compares the chance of a negative result under the target condition with the chance of a negative result without it. It is not the reciprocal of LR plus, which uses sensitivity/(1−specificity). The result actually observed determines which ratio belongs in the update.
Work a hypothetical rate example
Take pre-test probability 10%, sensitivity 90% and specificity 95%. A negative result has LR− = 0.1/0.95 = 2/19. Pre-test odds are 1/9, so post-test odds are 2/171. Converting odds to probability gives 2/173, approximately 1.1561%. This is an educational model calculation, not an individual diagnostic conclusion.
Check the direct probability route
The target-condition-and-negative contribution is 0.1×0.1 = 0.01. The no-condition-and-negative contribution is 0.9×0.95 = 0.855. Dividing 0.01 by their total 0.865 reproduces 2/173. This denominator check helps catch use of the wrong result likelihood.
Keep applicability separate from arithmetic
The Post-Test Probability Calculator supports both rate inputs and a known likelihood ratio. Test protocol, population and reference-standard differences can affect whether published rates are appropriate. A posterior is not a treatment instruction. The input-choice guide explains why an LR alone does not identify the probability of receiving the result. The Sensitivity and Specificity Calculator instead starts from observed validation counts to estimate the rates.
Check the model behind your result
Use the Post-Test Probability Calculator for the supported calculation and review its stated assumptions before interpreting the output. Find related tools in the Statistics category, or browse the GreenCalc homepage for other calculation topics.
By GreenCalc Editorial Team · Updated 2026-10-26