Linked Life Data

16133882

Source:http://linkedlifedata.com/resource/pubmed/id/16133882

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2005-8-31
pubmed:abstractText
Using local kappa coefficients, we develop a method to assess the agreement between two discrete survival times that are measured on the same subject by different raters or methods. We model the marginal distributions for the two event times and local kappa coefficients in terms of covariates. An estimating equation is used for modeling the marginal distributions and a pseudo-likelihood procedure is used to estimate the parameters in the kappa model. The performance of the estimation procedure is examined through simulations. The proposed method can be extended to multivariate discrete survival distributions.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1380-7870
pubmed:author
pubmed:issnType
Print
pubmed:volume
11
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
309-32
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Modeling the agreement of discrete bivariate survival times using kappa coefficient.
pubmed:affiliation
Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA. yguo2@sph.emory.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural