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

Research output: Contribution to journalJournal articlepeer-review

<mark>Journal publication date</mark>1/10/2006
<mark>Journal</mark>Journal of the Royal Statistical Society: Series A Statistics in Society
Issue number4
Number of pages20
Pages (from-to)681-700
Publication StatusPublished
<mark>Original language</mark>English


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.

Bibliographic note

RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research