Drawing upon the recent explosion of research in the field, adiverse group of scholars surveys the latest strategies for solvingecological inference problems, the process of trying to inferindividual behavior from aggregate data. The uncertainties andinformation lost in aggregation make ecological inference one ofthe most difficult areas of statistical inference, but theseinferences are required in many academic fields, as well as bylegislatures and the Courts in redistricting, marketing research bybusiness, and policy analysis by governments. This wide-rangingcollection of essays offers many fresh and important contributionsto the study of ecological inference.
【目录】
Introduction: information in ecological inference: anintroduction Gary King, Ori Rosen and Martin A. Tanner
Part I
1. Prior and likelihood choices in the analysis of ecological dataJonathan C. Wakefield
2. Information in aggregate data David G. Steel, Eric J. Beh andRaymond Lourenco Chambers
3. Using ecological inference for contextual research: whenaggregation bias is the solution as well as the problem D. StephenVoss
Part II
4. Extending King's ecological inference model to multipleelections using Markov chain Monte Carlo Jeffry B. Lewis
5. Ecological regression and ecological inference Bernard Grofmanand Samuel Merrill
6. Using prior information to aid ecological inference: a Bayesianapproach J. Kevin Corder and Christina Wolbrecht
7. An information theoretic approach to ecological estimation andinference George G. Judge, Douglas J. Miller and Wendy K. TamCho
8. Ecological panel inference from repeated cross sections RobEisinga, Ben Pelzer and Philip Hans B. F. Franses
Part III
9. Multi-party split-ticket voting estimation as an ecologicalinference problem Kenneth R. Benoit, Michael Laver and DanielaGiannetti
10. Ecological inference in the presence of temporal dependenceKevin M. Quinn
11. A spatial view of the ecological inference problem Carol A.Gotway and Linda J. Young
12. Places and relationships in ecological inference: uncoveringcontextual effects through a geographically weighted autoregressivemodel Ernesto Calvo and Marcelo Escolar
13. Ecological inference incorporating spatial dependenceSebastien Haneuse and Jonathan C. Wakefield
Part IV
14. A common framework for ecological inference in epidemiology,political science and sociology Ruth E. Salway and Jonathan C.Wakefield
15. A structured comparison of the Goodman regression, thetruncated normal, and the binomial-beta hierarchical methods forecological inference Rogério Silva de Mattos and ?lvaro Veiga
16. A comparison of the numerical properties of ei methods MicahAltman, Jeff Gill and Michael P. McDonald.
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