Which statement correctly describes the effect of a high positive likelihood ratio?

Prepare for the Critical Inquiry Exam 2 with flashcards and multiple-choice questions. Each question includes hints and explanations. Get ready for your exam!

Multiple Choice

Which statement correctly describes the effect of a high positive likelihood ratio?

Explanation:
A high positive likelihood ratio shows how much a positive test result shifts your belief toward disease. It quantifies how much more often a positive result occurs in people with the disease than in those without it. When LR+ is large, getting a positive result makes the post-test probability of disease rise substantially, because the odds after the test equal the odds before the test multiplied by that high LR+. In other words, a strong positive result is good at confirming disease. The other statements would only be true if the LR+ were near 1 or less than 1: a decrease in post-test probability after a positive result would require an LR+ below 1; calling the test not useful would imply LR+ around 1; and insensitivity relates to missed diagnoses (false negatives) rather than the effect of a positive result.

A high positive likelihood ratio shows how much a positive test result shifts your belief toward disease. It quantifies how much more often a positive result occurs in people with the disease than in those without it. When LR+ is large, getting a positive result makes the post-test probability of disease rise substantially, because the odds after the test equal the odds before the test multiplied by that high LR+. In other words, a strong positive result is good at confirming disease. The other statements would only be true if the LR+ were near 1 or less than 1: a decrease in post-test probability after a positive result would require an LR+ below 1; calling the test not useful would imply LR+ around 1; and insensitivity relates to missed diagnoses (false negatives) rather than the effect of a positive result.

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