Abstract #300727

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JSM 2002 Abstract #300727
Activity Number: 302
Type: Topic Contributed
Date/Time: Wednesday, August 14, 2002 : 10:30 AM to 12:20 PM
Sponsor: Social Statistics Section*
Abstract - #300727
Title: Handling Undecided Voters: Using Missing Data Methods in Election Forecasting
Author(s): Chen Quin Lam*+ and Elizabeth Stasny
Affiliation(s): Ohio State University and Ohio State University
Address: 404 Cockins Hall, 1958 Neil Avenue, Columbus, Ohio, 43210, USA
Keywords: Election Forecasting ; Random and non-random nonresponse ; Mean imputation ; Maximum likelihood estimation ; Sample surveys
Abstract:

This article considers different approaches to forecast election outcomes in the presence of incomplete data. Following a study, by Chang and Krosnick, using data from the Buckeye State Poll conducted in Ohio, where equal allocation of undecided respondents seem to improve forecasting, this article examines five missing-data methods used in sample survey literature to deal with the allocation of the undecided respondents. Maximum likelihood estimation is used to fit most of these models and it was found that some of them do reasonably well in forecasting election outcomes.

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