Ecological Inference (eBook, PDF)

New Methodological Strategies
Redaktion: King, Gary

• Format: PDF

Produktbeschreibung

Drawing upon the explosion of research in the field, a diverse group of scholars surveys strategies for solving ecological inference problems, the process of trying to infer individual behavior from aggregate data. The uncertainties and information lost in aggregation make ecological inference one of the most difficult areas of statistical inference, but these inferences are required in many academic fields, as well as by legislatures and the Courts in redistricting, marketing research by business, and policy analysis by governments. This wide-ranging collection of essays, first published in 2004, offers many important contributions to the study of ecological inference.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 13. September 2004
• Englisch
• ISBN-13: 9780511227592
• Artikelnr.: 38196065

Inhaltsangabe

Introduction: information in ecological inference: an introduction Gary
King, Ori Rosen and Martin A. Tanner; Part I: 1. Prior and likelihood
choices in the analysis of ecological data Jonathan C. Wakefield; 2.
Information in aggregate data David G. Steel, Eric J. Beh and Raymond
Lourenco Chambers; 3. Using ecological inference for contextual research:
when aggregation bias is the solution as well as the problem D. Stephen
Voss; Part II: 4. Extending King's ecological inference model to multiple
elections using Markov chain Monte Carlo Jeffry B. Lewis; 5. Ecological
regression and ecological inference Bernard Grofman and Samuel Merrill; 6.
Using prior information to aid ecological inference: a Bayesian approach J.
Kevin Corder and Christina Wolbrecht; 7. An information theoretic approach
to ecological estimation and inference George G. Judge, Douglas J. Miller
and Wendy K. Tam Cho; 8. Ecological panel inference from repeated cross
sections Rob Eisinga, Ben Pelzer and Philip Hans B. F. Franses; Part III:
9. Multi-party split-ticket voting estimation as an ecological inference
problem Kenneth R. Benoit, Michael Laver and Daniela Giannetti; 10.
Ecological inference in the presence of temporal dependence Kevin 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:
uncovering contextual effects through a geographically weighted
autoregressive model Ernesto Calvo and Marcelo Escolar; 13. Ecological
inference incorporating spatial dependence Sebastien 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, the
truncated normal, and the binomial-beta hierarchical methods for ecological
inference Rogério Silva de Mattos and Álvaro Veiga; 16. A comparison of the
numerical properties of ei methods Micah Altman, Jeff Gill and Michael P.
McDonald.