Abstract
The ecological inference problem is a famous longstanding puzzle that arises in many disciplines. The usual formulation in epidemiology is that we would like to quantify an exposure-disease association by obtaining disease rates among the exposed and unexposed, but only have access to exposure rates and disease rates for several regions. The problem is generally intractable, but can be attacked under the assumptions of King's (1997) extended technique if we can correctly specify a model for a certain conditional distribution. We introduce a procedure that it is a valid approach if either this original model is correct or if we can pose a correct model for a different conditional distribution. The new method is illustrated on data concerning risk factors for diabetes.
Disciplines
Epidemiology | Statistical Methodology | Statistical Theory
Suggested Citation
Rubin, Daniel B. and van der Laan, Mark J., "Doubly Robust Ecological Inference" (May 2008). U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 236.
https://biostats.bepress.com/ucbbiostat/paper236