Let's look at how to use Bayes' Theorem in everyday practice. First, a few principles:
The odds of an event are related to its probability, and these two entities can be easily computed from each other thusly:
Odds = Prob / (1-Prob)
pre-test odds × Likelihood Ratio = post-test odds
Thus all we need to estimate the post-test odds of a disease are its pre-test odds and the likelihood ratio (LR) for that test.
LRpositive test = Sensitivity / (1-Specificity)
LRnegative test = (1 - Sensitivity) / Specificity
Input the following information about your test (refresh page before trying a second set of numbers):
We will use the following table to estimate the likelihood of a meniscal tear, based on which of the following MR imaging features are present or absent.
In the following table, click in the box under LRpos if the feature is present, and click the box under LRneg if the feature is absent. Only click on the features you wish to consider. By doing this, we are collecting the likelihood ratios (LRpos, LRneg) that we will be using to determine post-test probability.