Post-Test Probability Calculator

Navigating the intricate world of medical testing and diagnostics might seem overwhelming. However, understanding terms like `Post-Test Probability` can clear away some of that fog. This page is dedicated to demystifying this concept and introducing you to a tool that simplifies its calculation. Dive in to get a grasp of this important statistic measure.

• How to use the Post-Test Probability Calculator?
• What is Post-Test Probability?
• Post-Test Probability Formulas

How to use the Post-Test Probability Calculator?

If you're looking to determine the probability of an event after considering new evidence, our calculator is your best bet. Here's a guide:

• Pre-test Probability (%) - This is your initial belief or the probability of the event before the test or evidence.
• Likelihood Ratio - A combined measure of the test's sensitivity and specificity.
• Calculate - The calculation will be done automatically, get the probability after testing based on the given input data.

What is Post-Test Probability?

Post-Test Probability, also known as posterior probability, offers insights into the likelihood of an event after receiving new evidence, such as a test result. It essentially answers the pivotal question: `Given the new data, what's the chance the event will occur?`

Rooted in Bayes' Theorem, it's the amalgamation of prior belief (pre-test probability) and the new evidence (likelihood). It plays a significant role in clinical diagnostics and other fields requiring probabilistic judgments after tests.

Post-Test Probability Formulas

The magic behind post-test probability lies in the Bayes' Theorem, a fundamental concept in probability theory and statistics. Here are the basics:

Post-Test Probability Formula:P(A|B) = \dfrac{P(B|A) \times P(A)}{P(B)}

• P(A|B) - Post-test probability
• P(B|A) - Likelihood of the test (test sensitivity)
• P(A) - Pre-test probability
• P(B) - Total probability of a positive test result