Linked Life Data

12973785

Source:http://linkedlifedata.com/resource/pubmed/id/12973785

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
19
pubmed:dateCreated
2003-9-15
pubmed:abstractText
Non-inferiority of a diagnostic test to the standard or the optimum test is a common issue in medical research. Often we want to determine if a new diagnostic test is as good as the standard reference test. Sometimes we are interested in an inexpensive test that may have an acceptably inferior sensitivity or specificity. While hypothesis testing procedures and sample size formulae for the equivalence of sensitivity or specificity alone have been proposed, very few studies have discussed simultaneous comparisons of both parameters. In this paper, we present three different testing procedures and sample size formulae for simultaneous comparison of sensitivity and specificity based on paired observations and with known disease status. These statistical procedures are then used to compare two classification rules that identify women for future osteoporotic fracture. Simulation experiments demonstrate that the new tests and sample size formulae give the appropriate type I and II error rates. Differences between our approach and the approach of Lui and Cumberland are discussed.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0277-6715
pubmed:author
pubmed:copyrightInfo
Copyright 2003 John Wiley & Sons, Ltd.
pubmed:issnType
Print
pubmed:day
15
pubmed:volume
22
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
3029-44
pubmed:dateRevised
2011-9-22
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
On the non-inferiority of a diagnostic test based on paired observations.
pubmed:affiliation
Department of Radiology, Box 0629, University of California, San Francisco, San Francisco, CA 94143-0629, USA. ying.lu@radiology.ucsf.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.