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Estimating attributable fraction in partially ecologic case-control studies.

Björk, Jonas LU and Strömberg, Ulf LU (2002) In Epidemiology 13(4). p.459-466
Abstract
Partially ecologic case-control studies combine group-level exposure data with individual-level data on disease status, group membership, and covariates. If the exposure measure is the exposure prevalence of various groups, the attributable fraction (AF; the estimated proportion of cases that are attributable to exposure) can be estimated by classifying all subjects in groups with exposure prevalence above zero as exposed. Such a threshold AF estimator ([AF]T) is unbiased in confounding-free situations if the threshold is 100% sensitive, but it might be imprecise. We propose an alternative AF estimator, [AF]L, for partially ecologic case-control studies under a linear model for the association between the exposure prevalence and the odds... (More)
Partially ecologic case-control studies combine group-level exposure data with individual-level data on disease status, group membership, and covariates. If the exposure measure is the exposure prevalence of various groups, the attributable fraction (AF; the estimated proportion of cases that are attributable to exposure) can be estimated by classifying all subjects in groups with exposure prevalence above zero as exposed. Such a threshold AF estimator ([AF]T) is unbiased in confounding-free situations if the threshold is 100% sensitive, but it might be imprecise. We propose an alternative AF estimator, [AF]L, for partially ecologic case-control studies under a linear model for the association between the exposure prevalence and the odds ratio. The proposed estimator can also be applied to situations in which covariate adjustment is necessary. [AF]T and [AF]L are compared with respect to precision and bias. [AF]L is also unbiased when the exposure prevalence is zero in the group(s) assessed as unexposed. Using [AF]L will consistently result in improved precision compared with [AF]T, although the results may not differ substantially. The 95% confidence intervals for both AF estimators show satisfactory coverage in bias-free exposure scenarios. Pronounced negative bias and decreased coverage result for both AF estimators even when small fractions (3-9%) of exposed subjects are included in the group assessed as unexposed. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Bias (Epidemiology), Case-Control Studies, Epidemiologic Methods, Occupational Exposure, Linear Models, Human, Odds Ratio, Sensitivity and Specificity
in
Epidemiology
volume
13
issue
4
pages
459 - 466
publisher
Wolters Kluwer Health/LWW
external identifiers
  • wos:000176378600015
  • scopus:0036285857
ISSN
1531-5487
DOI
10.1097/01.EDE.0000016860.40995.E9
language
English
LU publication?
yes
id
64d171e4-665f-44af-9b6e-e0824d169693 (old id 109101)
alternative location
http://www.ncbi.nlm.nih.gov:80/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12094102&dopt=Abstract
date added to LUP
2007-07-11 15:42:15
date last changed
2017-01-01 04:21:09
@article{64d171e4-665f-44af-9b6e-e0824d169693,
  abstract     = {Partially ecologic case-control studies combine group-level exposure data with individual-level data on disease status, group membership, and covariates. If the exposure measure is the exposure prevalence of various groups, the attributable fraction (AF; the estimated proportion of cases that are attributable to exposure) can be estimated by classifying all subjects in groups with exposure prevalence above zero as exposed. Such a threshold AF estimator ([AF]T) is unbiased in confounding-free situations if the threshold is 100% sensitive, but it might be imprecise. We propose an alternative AF estimator, [AF]L, for partially ecologic case-control studies under a linear model for the association between the exposure prevalence and the odds ratio. The proposed estimator can also be applied to situations in which covariate adjustment is necessary. [AF]T and [AF]L are compared with respect to precision and bias. [AF]L is also unbiased when the exposure prevalence is zero in the group(s) assessed as unexposed. Using [AF]L will consistently result in improved precision compared with [AF]T, although the results may not differ substantially. The 95% confidence intervals for both AF estimators show satisfactory coverage in bias-free exposure scenarios. Pronounced negative bias and decreased coverage result for both AF estimators even when small fractions (3-9%) of exposed subjects are included in the group assessed as unexposed.},
  author       = {Björk, Jonas and Strömberg, Ulf},
  issn         = {1531-5487},
  keyword      = {Bias (Epidemiology),Case-Control Studies,Epidemiologic Methods,Occupational Exposure,Linear Models,Human,Odds Ratio,Sensitivity and Specificity},
  language     = {eng},
  number       = {4},
  pages        = {459--466},
  publisher    = {Wolters Kluwer Health/LWW},
  series       = {Epidemiology},
  title        = {Estimating attributable fraction in partially ecologic case-control studies.},
  url          = {http://dx.doi.org/10.1097/01.EDE.0000016860.40995.E9},
  volume       = {13},
  year         = {2002},
}