#1
What does 'sensitivity' measure in a diagnostic test?
The proportion of true positives correctly identified
ExplanationMeasure of true positives correctly identified.
#2
Which of the following is an indication of a test with perfect discrimination capability?
AUC of 1.0
ExplanationIndicates perfect discrimination capability.
#3
What is the primary consequence of a diagnostic test with a high 'false negative rate'?
Increased likelihood of missing a disease
ExplanationIncreased likelihood of missing a disease.
#4
Which metric is used to assess the ability of a test to correctly identify those without the condition?
Specificity
ExplanationAbility to correctly identify those without the condition.
#5
What does a Receiver Operating Characteristic (ROC) curve illustrate?
The trade-off between test sensitivity and specificity
ExplanationIllustrates the trade-off between sensitivity and specificity.
#6
Which parameter is NOT directly affected by the prevalence of the disease in the population?
Specificity
ExplanationSpecificity is not directly affected by disease prevalence.
#7
In diagnostic test analysis, what does a high specificity and low sensitivity indicate?
The test is good at ruling in disease when the result is positive
ExplanationIndicates the test is good at ruling in disease when the result is positive.
#8
What is the impact of a high negative predictive value (NPV) in a diagnostic test?
It implies a high chance of disease absence when the test is negative
ExplanationImplies a high chance of disease absence when the test is negative.
#9
In the context of diagnostic tests, what does 'prevalence' affect?
Both positive and negative predictive values
ExplanationAffects both positive and negative predictive values.
#10
Which of the following best describes the 'positive predictive value' of a diagnostic test?
The probability that subjects with a positive test truly have the disease
ExplanationProbability that subjects with a positive test truly have the disease.
#11
What is the main advantage of using the Area Under the Curve (AUC) of an ROC curve?
It provides a single measure of test performance across all thresholds
ExplanationProvides a single measure of test performance across all thresholds.
#12
Which of the following best defines the 'likelihood ratio of a positive test' (LR+)?
The ratio of true positive rates to false positive rates
ExplanationRatio of true positive rates to false positive rates.
#13
What does 'negative likelihood ratio' (LR-) indicate in a diagnostic test?
The likelihood that a person with the disease tests negative
ExplanationLikelihood that a person with the disease tests negative.