The 2006 Cooperative Congressional Election Study

Abstract

A BSTRACT In 2006 Polimetrix, Inc. of Palo Alto, CA. fielded the Cooperative Congressional Election Study, the largest study of Congressional elections ever fielded in the US. The project was a joint venture of 38 universities and over 100 political scientists. In this paper, we detail the design and execution of the project, with special attention to the method by which the sample was generated. We show that the estimates from the Common Content of CCES outperform conventional estimates based on RDD phone surveys. We also argue that opt-in panels, internet surveys, and cooperative ventures like CCES provide cost-effective alternatives for social scientists under certain conditions. These types of surveys can provide reductions in RMSE over conventional methods when sample matching is used to ameliorate the biases that come with sampling from an opt-in panel.

Personality and Political Attitudes: Relationships across Issue Domains and Political Contexts

“…Finally, weights were calculated to adjust the final sample to reflect the national public on these demographic and other characteristics (including correcting for the oversampling of battleground states). For more detailed information on this type of survey and sampling technique, see Vavreck and Rivers (2008). In concrete terms, the weighted CCAP sample December 17, 2007 and January 3, 2008.…”

How the Gender of U.S. Senators Influences People’s Understanding and Engagement in Politics

“…A matched sampling methodology was utilized, matching key characteristics of a true representative sample of the U.S. population. According to Vavreck and Rivers (2008), the method of sample matching simultaneously reduces bias, improves efficiency and is a cost-effective method for constructing samples with minimal bias.…”

Journal of Applied Communications 100(3) Full Issue

“…Non-probability samples are commonly used in public opinion research to make population estimates and in this case was the best way to reach the population of interest: high water users. Although there are limitations in being able to generalize non-probability samples, they have been shown to yield results as good as, or even better than, probabilitybased samples (Abate, 2008;Twyman, 2008;Vavreck & Rivers, 2008). The researchers fully acknowledge the limitations of opt-in panels and the lack of coverage associated with on-line survey designs.…”

“…Non-probability samples are often used in public opinion research to make population estimates . While non-probability samples require adjustments for nonrandom selection and nonresponse, previous literature has shown non-probability samples have yielded results that are as good as or even better than probability-based samples (Abate, 1998;Twyman, 2008;Vavreck & Rivers, 2008).…”