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Reducing bias in ecological studies: an evaluation of different methodolgies.

Lancaster, Gillian and Green, Mick and Lane, Steven (2006) Reducing bias in ecological studies: an evaluation of different methodolgies. Journal of the Royal Statistical Society Series A (Statistics in Society), 169 (4). pp. 681-700. ISSN 1467-985X

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Abstract

Summary. Statistical methods of ecological analysis that attempt to reduce ecological bias are empirically evaluated to determine in which circumstances each method might be practicable. The method that is most successful at reducing ecological bias is stratified ecological regression. It allows individual level covariate information to be incorporated into a stratified ecological analysis, as well as the combination of disease and risk factor information from two separate data sources, e.g. outcomes from a cancer registry and risk factor information from the census sample of anonymized records data set. The aggregated individual level model compares favourably with this model but has convergence problems. In addition, it is shown that the large areas that are covered by local authority districts seem to reduce between-area variability and may therefore not be as informative as conducting a ward level analysis. This has policy implications because access to ward level data is restricted.

Item Type: Article
Journal or Publication Title: Journal of the Royal Statistical Society Series A (Statistics in Society)
Additional Information: RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research
Subjects: Q Science > QA Mathematics
Departments: Faculty of Science and Technology > Mathematics and Statistics
ID Code: 2469
Deposited By: ep_importer
Deposited On: 29 Mar 2008 17:35
Refereed?: Yes
Published?: Published
Last Modified: 09 Oct 2013 15:17
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/2469

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