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Efficiency of two-phase methods with focus on a planned population-based case-control study on air pollution and stroke

Oudin, Anna LU ; Björk, Jonas LU and Strömberg, Ulf LU (2007) In Environmental Health 6(34).
Abstract
ABSTRACT: We plan to conduct a case-control study to investigate whether exposure to nitrogen dioxide (NO2) increases the risk of stroke. In case-control studies, selective participation can lead to bias and loss of efficiency. A two-phase design can reduce bias and improve efficiency by combining information on the non-participating subjects with information from the participating subjects. In our planned study, we will have access to individual disease status and data on NO2 exposure on group (area) level for a large population sample of Scania, southern Sweden. A smaller sub-sample will be selected to the second phase for individual-level assessment on exposure and covariables. In this paper, we simulate a case-control study based on... (More)
ABSTRACT: We plan to conduct a case-control study to investigate whether exposure to nitrogen dioxide (NO2) increases the risk of stroke. In case-control studies, selective participation can lead to bias and loss of efficiency. A two-phase design can reduce bias and improve efficiency by combining information on the non-participating subjects with information from the participating subjects. In our planned study, we will have access to individual disease status and data on NO2 exposure on group (area) level for a large population sample of Scania, southern Sweden. A smaller sub-sample will be selected to the second phase for individual-level assessment on exposure and covariables. In this paper, we simulate a case-control study based on our planned study. We develop a two-phase method for this study and compare the performance of our method with the performance of other two-phase methods. METHODS: A two-phase case-control study was simulated with a varying number of first- and second-phase subjects. Estimation methods: Method 1: Effect estimation with second-phase data only. Method 2: Effect estimation by adjusting the first-phase estimate with the difference between the adjusted and unadjusted second-phase estimate. The first-phase estimate is based on individual disease status and residential address for all study subjects that are linked to register data on NO2-exposure for each geographical area. Method 3: Effect estimation by using the expectation-maximization (EM) algorithm without taking area-level register data on exposure into account. Method 4: Effect estimation by using the EM algorithm and incorporating group-level register data on NO2-exposure. RESULTS: The simulated scenarios were such that, unbiased or marginally biased (< 7 %) odds ratio (OR) estimates were obtained with all methods. The efficiencies of method 4, are generally higher than those of methods 1 and 2. The standard errors in method 4 decreased further when the case/control ratio is above one in the second phase. For all methods, the standard errors do not become substantially reduced when the number of first-phase controls is increased. CONCLUSION: In the setting described here, method 4 had the best performance in order to improve efficiency, while adjusting for varying participation rates across areas. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Environmental Health
volume
6
issue
34
publisher
BioMed Central
external identifiers
  • pmid:17988388
  • wos:000252362600001
  • scopus:37849004595
ISSN
1476-069X
DOI
10.1186/1476-069X-6-34
language
English
LU publication?
yes
id
d285208e-2625-4df1-8ac7-da5a55b78da7 (old id 1139873)
date added to LUP
2008-08-21 09:59:56
date last changed
2017-01-01 07:02:47
@article{d285208e-2625-4df1-8ac7-da5a55b78da7,
  abstract     = {ABSTRACT: We plan to conduct a case-control study to investigate whether exposure to nitrogen dioxide (NO2) increases the risk of stroke. In case-control studies, selective participation can lead to bias and loss of efficiency. A two-phase design can reduce bias and improve efficiency by combining information on the non-participating subjects with information from the participating subjects. In our planned study, we will have access to individual disease status and data on NO2 exposure on group (area) level for a large population sample of Scania, southern Sweden. A smaller sub-sample will be selected to the second phase for individual-level assessment on exposure and covariables. In this paper, we simulate a case-control study based on our planned study. We develop a two-phase method for this study and compare the performance of our method with the performance of other two-phase methods. METHODS: A two-phase case-control study was simulated with a varying number of first- and second-phase subjects. Estimation methods: Method 1: Effect estimation with second-phase data only. Method 2: Effect estimation by adjusting the first-phase estimate with the difference between the adjusted and unadjusted second-phase estimate. The first-phase estimate is based on individual disease status and residential address for all study subjects that are linked to register data on NO2-exposure for each geographical area. Method 3: Effect estimation by using the expectation-maximization (EM) algorithm without taking area-level register data on exposure into account. Method 4: Effect estimation by using the EM algorithm and incorporating group-level register data on NO2-exposure. RESULTS: The simulated scenarios were such that, unbiased or marginally biased (&lt; 7 %) odds ratio (OR) estimates were obtained with all methods. The efficiencies of method 4, are generally higher than those of methods 1 and 2. The standard errors in method 4 decreased further when the case/control ratio is above one in the second phase. For all methods, the standard errors do not become substantially reduced when the number of first-phase controls is increased. CONCLUSION: In the setting described here, method 4 had the best performance in order to improve efficiency, while adjusting for varying participation rates across areas.},
  articleno    = {(8 s)},
  author       = {Oudin, Anna and Björk, Jonas and Strömberg, Ulf},
  issn         = {1476-069X},
  language     = {eng},
  number       = {34},
  publisher    = {BioMed Central},
  series       = {Environmental Health},
  title        = {Efficiency of two-phase methods with focus on a planned population-based case-control study on air pollution and stroke},
  url          = {http://dx.doi.org/10.1186/1476-069X-6-34},
  volume       = {6},
  year         = {2007},
}