Bibliographic record and links to related information available from the Library of Congress catalog
Information from electronic data provided by the publisher. May be incomplete or contain other coding.
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 Roge;rio Silva de Mattos and Álvaro Veiga 16. A comparison of the numerical properties of ei methods Micah Altman, Jeff Gill and Michael P. McDonald.