title: Hierarchical models for combining ecological and case-control data.
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.
authors: Center for Health Studies, Group Health Cooperative, Seattle, Washington 98101, USA. haneuse.s@ghc.org
authors: Sebastien J-P A
authors: SJ
authors: Haneuse
authors: Jonathan C
authors: JC
authors: Wakefield
mesh_terms: D000293:Adolescent; D016022:Case-Control Studies; D004463:Ecology; D006801:Humans; D007223:Infant; D007226:Infant Mortality; D008913:Minority Groups; D015233:Models, Statistical; D009035:Mothers; D009657:North Carolina; D012307:Risk Factors