Linked Life Data

8241375

Source:http://linkedlifedata.com/resource/pubmed/id/8241375

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
1993-12-29
pubmed:abstractText
Bruzzi et al. (1985, American Journal of Epidemiology 122, 904-914) provided a general logistic-model-based estimator of the attributable fraction for case-control data, and Benichou and Gail (1990, Biometrics 46, 991-1003) gave an implicit-delta-method variance formula for this estimator. The Bruzzi et al. estimator is not, however, the maximum likelihood estimator (MLE) based on the model, as it uses the model only to construct the relative risk estimates, and not the covariate-distribution estimate. We here provide maximum likelihood estimators for the attributable fraction in cohort and case-control studies, and their asymptotic variances. The case-control estimator generalizes the estimator of Drescher and Schill (1991, Biometrics 47, 1247-1256). We also present a limited simulation study which confirms earlier work that better small-sample performance is obtained when the confidence interval is centered on the log-transformed point estimator rather than the original point estimator.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0006-341X
pubmed:author
pubmed:issnType
Print
pubmed:volume
49
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
865-72
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
1993
pubmed:articleTitle
Maximum likelihood estimation of the attributable fraction from logistic models.
pubmed:affiliation
Department of Epidemiology, UCLA School of Public Health 90024-1772.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.