Year: 1996
Type: book-review
Abstract: In our never-ending struggle to evaluate scientific data, an important study component is the critique of the steps used to collect or to interpret data.If the steps or tests used to differentiate data points are appropriate, then the differences or similarities between data become apparent.If tests are not chosen or designed appropriately, subtle - differences become indistinct or blurred.The more efficiently that a test can separate similar-but-different data points, the better the test.Obviously, the more a test lumps dissimilar data points, the less helpful the test.The accuracy of a test addresses this issue of differentiation.Accuracy reflects the number of data points or variates that are correctly identified by a test.An accurate test is not &dquo;fooled&dquo; by similar-but-different variates; it can differentiate positives and negatives.The Lachman test for ACL insufficiency can be used to examine the issue of test accuracy.If, for instance, the Lachman test can be performed in such a way that those knees with excessive secondary restraint laxity, hypermobility, or the upper ranges of normal anterior tibial translation can be differentiated from those with a torn ACL, then the Lachman test would be described as an accurate test for a torn ACL.If, however, the test cannot separate those knees with a torn ACL and excessive muscle tightness, intact second- ary restraints, and minimal increases in anterior tibial translation from normal, loose knees, the test would not be considered accurate for this lesion.Accuracy should be differentiated from precision, which deals with repeated measures.For instance, if a knee has 3 mm of anterior tibial translation but three arthrometer measurements yield 3.1, 3.2, and 3.3 mm, the precision of that measurement is within 0.3 mm.Accuracy, on
Institution: University of Michigan
Language: Spanish
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2604047701