Estimating attributable fraction in partially ecologic case-control studies.
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/109101
- author
- Björk, Jonas LU and Strömberg, Ulf LU
- organization
- publishing date
- 2002
- 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
- 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
- 2016-04-01 11:35:21
- date last changed
- 2022-01-26 07:20:41
@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}}, keywords = {{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}}, series = {{Epidemiology}}, title = {{Estimating attributable fraction in partially ecologic case-control studies.}}, url = {{http://dx.doi.org/10.1097/01.EDE.0000016860.40995.E9}}, doi = {{10.1097/01.EDE.0000016860.40995.E9}}, volume = {{13}}, year = {{2002}}, }