What is the likelihood ratio of a lab test?

Study for the ACVPM Epidemiology and Biostatistics Exam. Prepare with flashcards and multiple choice questions, with hints and explanations for each. Be exam-ready!

Multiple Choice

What is the likelihood ratio of a lab test?

A likelihood ratio for a lab test tells you how much more likely a given test result is in someone with the disease compared with someone without it. For a positive result, it compares P(test positive | disease) to P(test positive | no disease). Since sensitivity is P(T+ | D+) and 1 − specificity is P(T+ | D−), the positive likelihood ratio is sensitivity divided by (1 − specificity). This number shows how the odds of disease shift after a positive test and is the bridge between pretest probability and post-test probability when using Bayes’ updating. The other options don’t capture this definition: true positives to false positives isn’t a standard diagnostic measure, specificity to sensitivity isn’t the correct ratio, and the product of likelihood and prior relates to Bayes’ theorem but is not the likelihood ratio itself.

A likelihood ratio for a lab test tells you how much more likely a given test result is in someone with the disease compared with someone without it. For a positive result, it compares P(test positive | disease) to P(test positive | no disease). Since sensitivity is P(T+ | D+) and 1 − specificity is P(T+ | D−), the positive likelihood ratio is sensitivity divided by (1 − specificity). This number shows how the odds of disease shift after a positive test and is the bridge between pretest probability and post-test probability when using Bayes’ updating. The other options don’t capture this definition: true positives to false positives isn’t a standard diagnostic measure, specificity to sensitivity isn’t the correct ratio, and the product of likelihood and prior relates to Bayes’ theorem but is not the likelihood ratio itself.

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