Which statement about likelihood ratios is true?

Unlock all questions

This demo includes only 20 questions. Upgrade to access hundreds of questions, flashcards, exam simulations, and disable ads.

Full question bankExam simulationsFlashcards
From $24.99Unlock all

Prepare effectively for the Community Health Exam II. Engage with comprehensive multiple-choice questions and detailed explanations. Ace your exam!

Multiple Choice

Which statement about likelihood ratios is true?

Explanation:
Likelihood ratios show how a test result changes the odds of having the disease. The positive likelihood ratio tells you how much the odds increase when the test is positive, and the negative likelihood ratio tells you how much the odds decrease when the test is negative. By definition, a positive result that truly relates to disease makes LR+ greater than 1, meaning it raises the odds, while a negative result that truly relates to absence of disease makes LR- less than 1, meaning it lowers the odds. So a positive test increases odds (LR+ > 1) and a negative test decreases odds (LR- < 1).

Likelihood ratios show how a test result changes the odds of having the disease. The positive likelihood ratio tells you how much the odds increase when the test is positive, and the negative likelihood ratio tells you how much the odds decrease when the test is negative. By definition, a positive result that truly relates to disease makes LR+ greater than 1, meaning it raises the odds, while a negative result that truly relates to absence of disease makes LR- less than 1, meaning it lowers the odds. So a positive test increases odds (LR+ > 1) and a negative test decreases odds (LR- < 1).

More Multiple Choice Questions
Subscribe

Get the latest from Examzify

You can unsubscribe at any time. Read our privacy policy