Assessing Screening and Diagnostic Tests

William H. Holmes () and William C. Rinaman ()
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William H. Holmes: Le Moyne College

Chapter 8 in Statistical Literacy for Clinical Practitioners, 2014, pp 205-231 from Springer

Abstract: Abstract Clinicians often use screening and diagnostic tests to identify asymptomatic patients, confirm diagnoses or assess treatment effectiveness. The usefulness of these tests depends on their ability to correctly classify patients as having or not having a particular disease. This ability is assessed by determining the extent to which a test’s classifications agree with those of a criterion or gold standard. This chapter reviews several measures of agreement, including the test’s positive and negative predictive values, its true positive rate or sensitivity, its true negative rate or specificity, and the ratio of its true positive rate to its false positive rate, or likelihood ratio. The chapter concludes with a discussion of how a receiver operating characteristic (ROC) curve is used to evaluate the accuracy of a test that generates a range of quantitative values, and to select a cutoff value that optimizes sensitivity and specificity.

Keywords: Prostate Cancer; Likelihood Ratio; Receiver Operating Characteristic Curve; Positive Predictive Value; False Positive Rate (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-12550-3_8

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DOI: 10.1007/978-3-319-12550-3_8

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