Sources of bias in ecological studiesof non-rare events |
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Authors: | Email author" target="_blank">Ruth?SalwayEmail author Jonathan?Wakefield |
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Institution: | (1) Department of Mathematical Sciences, University of Bath, Bath, UK;(2) Departments of Statistics and Biostatistics, University of Washington, Seattle, USA |
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Abstract: | Ecological studies investigate relationships at the level of the group, rather than at the level of the individual. Although
such studies are a common design in epidemiology, it is well-known that estimates may be subject to ecological bias. Most
discussion of ecological bias has focused on rare disease events, where the tractability of the loglinear model allows some
characterization of the nature of different biases. This paper concentrates on non-rare events, where the Poisson approximation
to the binomial distribution is not appropriate. We limit the discussion to bias that arises from within-area variability
in exposures and confounders. Our aims are to investigate the likely sizes and directions of bias and, where possible, to
suggest methods for controlling the bias or for addressing the sensitivity of inference to assumptions on the nature of the
bias. We illustrate that for non-rare events it is much more difficult to characterize the direction of bias than in the rare
case. A series of simple numerical examples based on a chronic study of respiratory health illustrate the ideas of the paper. |
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Keywords: | aggregate data air pollution confounding ecological fallacy within-area variability |
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