Can Registration-Based Sampling Improve the Accuracy of Midterm Election Forecasts?

Authors: Green, Donald P.; Gerber, Alan S.

Source: Public Opinion Quarterly, Volume 70, Number 2, 2006 , pp. 197-223(27)

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Abstract:

We compare the predictive accuracy of preelection polls using two types of sampling frames, random digit dialing (RDD) and registration-based sampling (RBS). The latter involves stratified random sampling from voter registration lists. In order to assess the accuracy with which RDD and RBS predict election outcomes, we collaborated with the Washington Post, Quinnipiac, and CBS News polls, which conducted parallel RDD and RBS surveys in Maryland, New York, Pennsylvania, and South Dakota prior to the November 5, 2002, elections. The results suggest that in the gubernatorial and congressional elections studied, RBS performed as well, if not better, than RDD, both in terms of forecasting accuracy and cost.

Document Type: Research article

DOI: http://dx.doi.org/10.1093/poq/nfj022

Publication date: 2006-01-01

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Published since 1937, Public Opinion Quarterly is among the most frequently cited journals of its kind. Such interdisciplinary leadership benefits academicians and all social science researchers by providing a trusted source for a wide range of high quality research. POQ selectively publishes important theoretical contributions to opinion and communication research, analyses of current public opinion, and investigations of methodological issues involved in survey validity - including questionnaire construction, interviewing and interviewers, sampling strategy, and mode of administration. The theoretical and methodological advances detailed in pages of POQ ensure its importance as a research resource.