Linked Life Data

17613652

Source:http://linkedlifedata.com/resource/pubmed/id/17613652

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2007-7-6
pubmed:abstractText
We propose a new approach to evaluating agreement between two observers making binary observations on a set of subjects. This approach compares the probability of disagreement (or discordance) between the observers to the probability of disagreement between replicated observations made by the same observer on the same subject. We consider two situations: (1) a symmetric assessment of agreement between two observers, and (2) an assessment of the agreement of a new observer with an imperfect "gold standard". We develop a nonparametric method for estimation of the new agreement coefficients when observers make replicated readings on each subject. The reliability of the estimation method is examined via a simulation study. Data from a study aimed at determining the validity of diagnosis of breast cancer based on mammograms is used to illustrate the new concepts and methods.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1054-3406
pubmed:author
pubmed:issnType
Print
pubmed:volume
17
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
757-66
pubmed:dateRevised
2007-12-3
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Assessing observer agreement in studies involving replicated binary observations.
pubmed:affiliation
Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, USA. mhaber@sph.emory.edu
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural