Positive and negative predictive value, likelihood ratios, and ROC curve interpretation as cloze cards with each formula and term defined.
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- Sensitivity is the proportion of people with the disease who test ____.
- positive
- Specificity is the proportion of people without the disease who test ____.
- negative
- Positive predictive value (PPV) is the proportion of people with a ____ test result who actually have the disease.
- positive
- Negative predictive value (NPV) is the proportion of people with a ____ test result who actually do not have the disease.
- negative
- PPV equals true positives divided by ____.
- (true positives + false positives)
- NPV equals true negatives divided by ____.
- (true negatives + false negatives)
- Sensitivity equals true positives divided by ____.
- (true positives + false negatives)
- Specificity equals true negatives divided by ____.
- (true negatives + false positives)
- If disease prevalence increases while sensitivity and specificity stay fixed, what happens to PPV?
- PPV increases
- If disease prevalence increases while sensitivity and specificity stay fixed, what happens to NPV?
- NPV decreases
- Sensitivity and specificity are intrinsic test properties that do ____ change with disease prevalence.
- not
- The positive likelihood ratio (LR+) equals sensitivity divided by ____.
- (1 - specificity)
- The negative likelihood ratio (LR-) equals (1 - sensitivity) divided by ____.
- specificity
- An LR+ greater than ____ increases the probability that a patient has the disease.
- 1
- An LR- less than ____ decreases the probability that a patient has the disease.
- 1