Author's Keywords: ecological inference, standard errors, maximum entropy, ticket-splitting, New Zealand, simulation	Convention Convention is an application service for managing large or small academic conferences, annual meetings, and other types of events! Submission - Custom fields, multiple submission types, tracks, audio visual, multiple upload formats, automatic conversion to pdf. Review - Peer Review, Bulk reviewer assignment, bulk emails, ranking, z-score statistics, and multiple worksheets! Reports - Many standard and custom reports generated while you wait. Print programs with participant indexes, event grids, and more! Scheduling - Flexible and convenient grid scheduling within rooms and buildings. Conflict checking and advanced filtering. Communication - Bulk email tools to help your administrators send reminders and responses. Use form letters, a message center, and much more! Management - Search tools, duplicate people management, editing tools, submission transfers, many tools to manage a variety of conference management headaches! Click here for more information.
Association: Name: American Political Science Association URL: http://www.apsanet.org
Citation: URL: http://www.allacademic.com/meta/p42445_index.html Direct Link: HTML Code:

Elff, Martin. and Gschwend, Thomas. "Making Ecological Inference for R x C Tables easy - Standard Errors for EMax" Paper presented at the annual meeting of the American Political Science Association, Marriott Wardman Park, Omni Shoreham, Washington Hilton, Washington, DC, Sep 01, 2005 <Not Available>. 2011-03-14 <http://www.allacademic.com/meta/p42445_index.html>

Elff, M. and Gschwend, T. , 2005-09-01 "Making Ecological Inference for R x C Tables easy - Standard Errors for EMax" Paper presented at the annual meeting of the American Political Science Association, Marriott Wardman Park, Omni Shoreham, Washington Hilton, Washington, DC Online <APPLICATION/PDF>. 2011-03-14 from http://www.allacademic.com/meta/p42445_index.html

Publication Type: Conference Paper/Unpublished Manuscript Review Method: Peer Reviewed Abstract: For most substantive relevant ecological inference problems scholars face a R x C table from which only the marginals can be observed. We argue that most frequent used ecological inference methods are computationally demanding and are inefficient since they do not make use of all the information that is available. We take a fresh look at an estimator that was precisely developed for these kinds of problems: EMax. This estimator utilizes more available information at the estimation stage than previous ecological inference estimators in the literature. As methodological innovation that remedy the main disadvantage of EMax in substantive applications, we derive model-based standard errors. Further we examine their validity by means of a simulation study and demonstrate their use in an application to the estimation of split-ticket voting in New Zealand voting districts.

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Evaluating Various Methods of Standard Error Estimation for Use with the Current Population Survey’s Public Use Data

Estimating Cross-Over Voting in 2005 Jackson, Miss. Democratic Mayoral Primary via Ecological Inference