Skip to Content
Interactive Textbook on Clinical Symptom Research Logo


Home Button

Tools for Decision Making Sections
Author Bio
Introduction
Probability Theory
Case Study 1: Patient History
Currently selected section: Bayes' Theorem
Methods for Estimating Pre-test Probability
Estimating Likelihood Ratios
Sensitivity and Specificity
Interpreting Test Results
Calculating Post-test Probabilities
Post-test Probabilities in Clinical Practice
Conclusions: Case Study 1
Part II
Part III
References

 

Chapter 14: Tools for Decision Making: Case Study 1: Bayes' Theorem

        

 

You Answered:

Selection CThe likelihood ratio of a test is a standardized number that locks in the meaning of the test result.

Incorrect


The correct answer is: (A).

Bayes' theorem tells us that the likelihood ratio of a test is the only characteristic of the test that influences the meaning of the test result.



      Back to Question