Selecting and interpreting diagnostic tests

Interpreting Diagnostic Tests Using Probability

These notes detail my 40-minute lecture given 11 June 1995 as part of the Seventh Annual Intensive Review of Internal Medicine, a symposium conducted by the Cleveland Clinic. I was asked to review how probability is used with diagnostic testing. Our main question is: How can diagnostic results and other information about a patient be used to estimate the chance that he/she has a particular “dis...

Assessing the Validity of Diagnostic Tests

STATISTICAL DEVELOPMENTS AND APPLICATIONS Diagnosing Tests: Using and Misusing Diagnostic and Screening Tests STREINER DIAGNOSTIC TESTS

Tests can be used either diagnostically (i.e., to confirm or rule out the presence of a condition in people suspected of having it) or as a screening instrument (determining who in a large group of people has the condition and often when those people are unaware of it or unwilling to admit to it). Tests that may be useful and accurate for diagnosis may actually do more harm than good when used ...

Probabilistic analysis of global performances of diagnostic tests: interpreting the Lorenz curve-based summary measures.

Several indices based on the receiver operating characteristic curve (ROC curve) have previously been found to possess probabilistic interpretations. However, these interpretations are based on some unrealistic diagnostic scenarios. In this paper, the author presents a new approach using the Lorenz curve. The author found that the summary indices of the Lorenz curve, that is, the Pietra index a...

Specification and Diagnostic Tests

Each test procedure described below involves the specification of a null hypothesis, which is the hypothesis under test. Output from a test command consists of the sample values of one or more test statistics and their associated probability numbers (p-values). The latter indicate the probability of obtaining a test statistic whose absolute value is greater than or equal to that of the sample s...