Linked Life Data

10363342

Source:http://linkedlifedata.com/resource/pubmed/id/10363342

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
1999-7-27
pubmed:abstractText
We develop parametric methods for analysing interval-censored data when examination and survival times are not independent. The hazard function is modelled by introducing individual frailties related to the frequency of examinations. Model parameters may be obtained by direct maximization of the marginal log-likelihood. We develop a simpler approximate method in which the frailties are estimated by empirical Bayes. The two approaches are equivalent asymptotically as the number of examinations on each individual increases. Simulations suggest that the approximate method is adequate for estimating regression parameters even when the number of examinations on each individual is small. The methods are used to estimate age and period effects on HIV incidence in a cohort of repeat attenders at genito-urinary clinics in London, U.K.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0277-6715
pubmed:author
pubmed:issnType
Print
pubmed:day
30
pubmed:volume
18
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1235-48
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Interval-censored survival data with informative examination times: parametric models and approximate inference.
pubmed:affiliation
Statistics Department, Faculty of Mathematics and Computing, Open University, Milton Keynes, U.K.
pubmed:publicationType
Journal Article