Linked Life Data

21279545

Source:http://linkedlifedata.com/resource/pubmed/id/21279545

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2011-6-13
pubmed:abstractText
Copula models for multivariate lifetimes have become widely used in areas such as biomedicine, finance and insurance. This paper fills some gaps in existing methodology for copula parameters and model assessment. We consider procedures based on likelihood and pseudolikelihood ratio statistics and introduce semiparametric maximum likelihood estimation leading to semiparametric versions. For cases where standard asymptotic approximations do not hold, we propose an efficient simulation technique for obtaining p-values. We apply these methods to tests for a copula model, based on embedding it in a larger copula family. It is shown that the likelihood and pseudolikelihood ratio tests are consistent even when the expanded copula model is misspecified. Power comparisons with two other tests of fit indicate that model expansion provides a convenient, powerful and robust approach. The methods are illustrated on an application concerning the time to loss of vision in the two eyes of an individual.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1572-9249
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
17
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
386-408
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Likelihood ratio procedures and tests of fit in parametric and semiparametric copula models with censored data.
pubmed:affiliation
Prosserman Centre for Health Research, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, ON, Canada. yilmaz@lunenfeld.ca
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't