Hierarchical related regression for combining aggregate and individual data in studies of socio-economic disease risk factors
Article first published online: 18 SEP 2007
DOI: 10.1111/j.1467-985X.2007.00500.x
Issue
Journal of the Royal Statistical Society: Series A (Statistics in Society)
Volume 171, Issue 1, pages 159–178, January 2008
Additional Information
How to Cite
Jackson, C., Best, A. N. and Richardson, S. (2008), Hierarchical related regression for combining aggregate and individual data in studies of socio-economic disease risk factors. Journal of the Royal Statistical Society: Series A (Statistics in Society), 171: 159–178. doi: 10.1111/j.1467-985X.2007.00500.x
Publication History
- Issue published online: 18 SEP 2007
- Article first published online: 18 SEP 2007
- [Received October 2005. Final revision March 2007]
- Abstract
- Article
- References
- Cited By
Keywords:
- Cardio-vascular disease;
- Contextual effects;
- Data synthesis;
- Ecological bias;
- Hierarchical models
Summary. To obtain information about the contribution of individual and area level factors to population health, it is desirable to use both data collected on areas, such as censuses, and on individuals, e.g. survey and cohort data. Recently developed models allow us to carry out simultaneous regressions on related data at the individual and aggregate levels. These can reduce ‘ecological bias’ that is caused by confounding, model misspecification or lack of information and increase power compared with analysing the data sets singly. We use these methods in an application investigating individual and area level sociodemographic predictors of the risk of hospital admissions for heart and circulatory disease in London. We discuss the practical issues that are encountered in this kind of data synthesis and demonstrate that this modelling framework is sufficiently flexible to incorporate a wide range of sources of data and to answer substantive questions. Our analysis shows that the variations that are observed are mainly attributable to individual level factors rather than the contextual effect of deprivation.