Hierarchical models for combining ecological and case-control data |
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Authors: | Haneuse Sebastien J-P A Wakefield Jonathan C |
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Institution: | Center for Health Studies, Group Health Cooperative, Seattle, Washington 98101, USA. haneuse.s@ghc.org |
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Abstract: | The ecological study design suffers from a broad range of biases that result from the loss of information regarding the joint distribution of individual-level outcomes, exposures, and confounders. The consequent nonidentifiability of individual-level models cannot be overcome without additional information; we combine ecological data with a sample of individual-level case-control data. The focus of this article is hierarchical models to account for between-group heterogeneity. Estimation and inference pose serious computational challenges. We present a Bayesian implementation based on a data augmentation scheme where the unobserved data are treated as auxiliary variables. The methods are illustrated with a dataset of county-specific infant mortality data from the state of North Carolina. |
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Keywords: | Auxiliary variables Biased sampling schemes Ecological fallacy Hierarchical models |
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