Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-27T10:08:48.418Z Has data issue: false hasContentIssue false
  • English
  • Français

Online Polls and Registration-Based Sampling: A New Method for Pre-Election Polling

Published online by Cambridge University Press:  04 January 2017

Michael J. Barber ,
Christopher B. Mann ,
J. Quin Monson  and
Kelly D. Patterson
Michael J. Barber
Affiliation:
Princeton University, 130 Corwin Hall, Princeton, NJ 08540. e-mail: barber@princeton.edu
Christopher B. Mann*
Affiliation:
Manship School of Mass Communication and Department of Political Science, Louisiana State University, 210 Hodges Hall, Baton Rouge, LA 70803
J. Quin Monson
Affiliation:
Department of Political Science, Brigham Young University, 745 SWKT, Provo, UT 84602. e-mail: Quin.Monson@byu.edu
Kelly D. Patterson
Affiliation:
Department of Political Science, Brigham Young University, 745 SWKT, Provo, UT 84602. e-mail: Kelly_Patterson@byu.edu
*
e-mail: cmann13@lsu.edu (corresponding author)
Get access Rights & Permissions [Opens in a new window]

Abstract

This article outlines a new method for surveys to study elections and voter attitudes. Pre-election surveys often suffer from an inability to identify and survey the likely electorate for the upcoming election. We propose a new and inexpensive method to conduct representative surveys of the electorate. We demonstrate the performance of our method in producing a representative sample of the future electorate that can be used to study campaign dynamics and many other issues. We compare pre-election outcome forecasts to election outcomes in seven primary and general election surveys conducted prior to the 2008 and 2010 primary and general elections in three states. The results indicate that the methodology produces representative samples, including in low-turnout elections such as primaries where traditional methods have difficulty consistently sampling the electorate. This new methodology combines Probability Proportional to Size (PPS) sampling, mailed invitation letters, and online administration of the questionnaire. The PPS sample is drawn based on a model employing variables from the publicly available voter file to produce a probability of voting score for each individual voter. The proposed method provides researchers a valuable tool to study the attitudes of the voting public.

Type
Symposium on Advances in Survey Methodology
Information
Political Analysis , Volume 22 , Issue 3 , Summer 2014 , pp. 321 - 335
Copyright
Copyright © The Author 2014. Published by Oxford University Press on behalf of the Society for Political Methodology 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Authors' note: We thank Anand Sohkey and his colleagues at University of Colorado—Boulder for their assistance in conducting the 2010 primary surveys in Colorado and Matthew Frei of the Center for the Study of Elections and Democracy (CSED) at Brigham Young University (BYU) for his assistance in administering the surveys. We thank Lonna Atkeson, Larry Bartels, John Love, Mark A. Schulman, the anonymous reviewers, and participants in a faculty research seminar at BYU for helpful comments. Previous versions of this paper were presented at the annual meetings of the American Association of Public Opinion Research in 2010 and 2011. This research would not have been possible without the generous support of CSED at BYU, the University of Colorado—Boulder, and the University of Miami. All errors are the responsibility of the authors. Supplementary materials for this article are available on the Political Analysis Web site. Replication data are available on the Political Analysis Dataverse at http://dx.doi.org/10.7910/DVN/22908.

References

Alvarez, R. Michael, Sherman, Robert P., and VanBeselaere, Carla. 2003. Subject acquisition for web-based surveys. Political Analysis 1: 23–43.Google Scholar
Ansolabehere, Stephen, and Hersh, Eitan. 2012. Misreporting, sample selection, and participation. Political Analysis 20: 437–59.Google Scholar
Atkeson, Lonna R., and Tafoya, Lorraine M. 2008. Surveying political activists: The effectiveness of a mixed mode survey design. Journal of Elections, Public Opinion & Parties 18: 367.Google Scholar
Atkeson, Lonna, Adams, Alex, Bryant, Lisa, Zilberman, Luciana, and Saunders, Kyle. 2011. Considering mixed mode surveys for questions in political behavior: Using the internet and mail to get quality data at reasonable costs. Political Behavior 33: 161–78.Google Scholar
Baker, Reg, Michael Brick, J., Bates, Nancy A., Battaglia, Mike, Couper, Mick P., Dever, Jill A., Gile, Krista J., and Tourangeau, Roger. 2013. Report of the AAPOR Task Force on Non-Probability Sampling. May 2013 (updated June 22, 2013). http://www.aapor.org/Reports1.htm (accessed September 18, 2013).Google Scholar
Baker, Reg, Blumberg, Stephen J., Michael Brick, J., Couper, Mick P., Courtright, Melanie, Michael Dennis, J., Dillman, Don, Frankel, Martin R., Garland, Philip, Groves, Robert M., Kennedy, Courtney, Krosnick, Jon, Lavrakas, Paul J., Lee, Sunghee, Link, Michael, Piekarski, Linda, Rao, Kumar, Thomas, Randall K., and Zahs, Dan. 2010. AAPOR Report on Online Panels. Public Opinion Quarterly 74: 711–81.Google Scholar
Barber, Michael J. 2013. Ideological donors, contribution limits, and the polarization of state legislatures. Presented at the Annual Meeting of the American Political Science Association.Google Scholar
Bartels, Larry. 1991. Constituency opinion and congressional policy making: The Reagan defense buildup. American Political Science Review 85: 457–74.Google Scholar
Berrens, Robert P., Bohara, Alok K., Jenkins-Smith, Hank, Silva, Carol, and Weimer, David L. 2003. The advent of internet surveys for political research: A comparison of telephone and internet samples. Political Analysis 11: 1–22.Google Scholar
Burden, Barry. 1997. Deterministic and probabilistic voting models. American Journal of Political Science 41: 1150–69.Google Scholar
Butler, Daniel, and Nickerson, David. 2011. Can learning constituency opinion affect how legislators vote? Results from a field experiment. Quarterly Journal of Political Science 6: 55–83.Google Scholar
Chang, LinChiat, and Krosnick, Jon. 2009. National surveys via RDD telephone interviewing versus the internet: Comparing sample representativeness and response quality. Public Opinion Quarterly 73: 641–78.Google Scholar
Chang, LinChiat, and Krosnick, Jon. 2010. Comparing oral interviewing with self-administered computerized questionnaires: An experiment. Public Opinion Quarterly 74: 154–67.Google Scholar
Couper, Mick P. 2000. Web surveys: A review of issues and approaches. Public Opinion Quarterly 64: 464–94.Google Scholar
Crespi, Irving. 1988. Pre-election polling: Sources of accuracy and error. New York. Russell Sage Foundation.Google Scholar
Dillman, Don A., and Christian, Leah M. 2005. Survey mode as a source of instability in responses across surveys. Field Methods 17: 30–52.Google Scholar
Dillman, Don A., Glenn, Phelps, Tortora, Robert, Swift, Karen, Kohrell, Julie, Berck, Jodi, and Messer, Benjamin L. 2009. Response rate and measurement differences in mixed-mode surveys using mail, telephone, interactive voice response (IVR) and the internet. Social Science Research 38: 1–18.Google Scholar
Fishbein, Martin, and Ajzen, Icek. 1975. Belief, attitude, intention, and behavior. Reading, MA: Addison-Wesley Publishing.Google Scholar
Freedman, Paul, and Goldstein, Ken. 1997. Building a probable electorate from pre-election polls: A two-stage approach. Public Opinion Quarterly 60: 574–87.Google Scholar
Frei, Matthew D., Quin Monson, J., Murray, Leah, and Patterson, Kelly D. 2012. Tea for only two: The ousting of Utah Senator Robert Bennett. In Tea Party Effects on 2010 U.S. Senate Elections: Stuck in the Middle to Lose, eds. Miller, William J. and Walling, Jeremy D., 105–20. Lanham, MD: Lexington Books.Google Scholar
Green, Donald P., and Gerber, Alan S. 2006. Can registration-based sampling improve the accuracy of midterm election forecasts? Public Opinion Quarterly 70: 197–223.Google Scholar
Gilens, Martin. 2012. Affluence and influence: Economic inequality and political power in America. Princeton, NJ: Princeton University Press.Google Scholar
Groves, Robert M. 2006. Non-response rates and non-response bias in household surveys. Public Opinion Quarterly 70: 646–75.Google Scholar
Groves, Robert M., and Peytcheva, Emilia. 2008. The impact of nonresponse rates on nonresponse bias. Public Opinion Quarterly 72: 167–89.Google Scholar
Hoek, Janet, and Daves, Robert P. 1997. Turnout prediction: A comparison of methodologies. Presented at the Annual Meeting of the American Association for Public Opinion Research, Norfolk, VA.Google Scholar
Jann, B. 2006. gsample: Stata module to draw a random sample. http://ideas.repec.org/c/boc/bocode/s456716.html (accessed February 8, 2012).Google Scholar
Juster, F. Thomas. 1960. Prediction and consumer buying intentions. American Economic Review 50: 604–22.Google Scholar
Karpowitz, Christopher F., King-Meadows, Tyson, Quin Monson, J., and Pope, Jeremy C. 2013. Carrying many credentials: Partisan, racial, and religious dynamics in the Utah Fourth District. Presented at the Annual Meeting of the Midwest Political Science Association.Google Scholar
Karpowitz, Christopher F., Quin Monson, J., Patterson, Kelly D., and Pope, Jeremy C. 2011. Tea time in America? The impact of the Tea Party movement on the 2010 midterm elections. PS: Political Science & Politics 44: 303–9.Google Scholar
Keeter, Scott, Miller, Carolyn, Kohut, Andrew, Groves, Robert M., and Presser, Stanley. 2000. Consequences of reducing nonresponse in a national telephone survey. Public Opinion Quarterly 64: 125–48.Google Scholar
Keeter, Scott, Kennedy, Courtney, Dimock, Michael, Best, Jonathan, and Craighill, Peyton. 2006. Gauging the impact of growing non-response on estimates from a national RDD telephone survey. Public Opinion Quarterly 70: 759–79.CrossRefGoogle Scholar
Larcinese, Valentino. 2007. Does political knowledge increase turnout? Evidence from the 1997 British general election. Public Choice 131: 387–411.Google Scholar
Lavrakas, Paul J. 1993. Telephone survey methods: Sampling, selection, and supervision. 2nd ed. Newbury Park, CA: Sage Publications.Google Scholar
Lohr, Sharon L. 2010. Sampling: Design and Analysis. 2nd ed. Boston: Brooks/Cole, Cengage Learning.Google Scholar
Malchow, Hal. 2008. Political Targeting. 2nd ed. Washington, DC: Predicted Lists LLC Publishing.Google Scholar
Malhotra, Neil, and Krosnick, Jon A. 2007. The effect of survey mode and sampling on inferences about political attitudes and behavior: Comparing the 2000 and 2004 ANES to internet surveys with nonprobability samples. Political Analysis 15: 286–323.Google Scholar
Mann, Christopher B. 2005. Do advance letters improve preelection forecast accuracy? Public Opinion Quarterly 69: 561–71.Google Scholar
Martin, Elizabeth, Traugott, Michael, and Kennedy, Courtney. 2005. A review and proposal for a new measure of poll accuracy. Public Opinion Quarterly 69: 342–69.Google Scholar
Perry, Paul. 1960. Election survey procedures of the Gallup poll. Public Opinion Quarterly 24: 531–42.Google Scholar
Perry, Paul. 1979. Certain problems in election survey methodology. Public Opinion Quarterly 43: 312–25.Google Scholar
Petrocik, John R. 1991. An algorithm for estimating turnout as a guide to predicting elections. Public Opinion Quarterly 55: 643–47.Google Scholar
Pew Research Center for the People and the Press. 2012. Assessing the representativeness of public opinion surveys. http://www.people-press.org/files/legacy-pdf/Assessing%20the%20Representativeness%20of%20Public%20Opinion%20Surveys.pdf (accessed August 5, 2012).Google Scholar
Peytchev, Andy, Baxter, Rodney K., and Carley-Baxter, Lisa R. 2009. Not all survey effort is equal: Reduction of non-response bias and non-response error. Public Opinion Quarterly 73: 785–806.Google Scholar
Rogers, Todd, and Aida, Masa. 2011. Vote self-prediction hardly predicts who will vote, and is (misleadingly) unbiased. American Politics Research. Published online before print September 5, 2013, doi: 10.1177/1532673X13496453.Google Scholar
Sanders, David, Clarke, Harold D., Stewart, Marianne C., and Whiteley, Paul. 2007. Does mode matter for modeling political choice? Evidence from the 2005 British Election Study. Political Analysis 15: 257–85.Google Scholar
Scheiber, Noam. 2012. The internal polls that made Mitt Romney think he'd win. New Republic November 30. 2012. http://www.newrepublic.com/blog/plank/110597/exclusive-the-polls-made-mitt-romney-think-hed-win (accessed December 1, 2012).Google Scholar
Silver, Brian D., Anderson, Barbara A., and Abramson, Paul R. 1986. Who overreports voting? American Political Science Review 80: 613–24.CrossRefGoogle Scholar
Sokhey, Anand E., and Djupe, Paul A. 2014. Name generation in interpersonal political network data: Results from a series of experiments. Social Networks 36: 147–61.Google Scholar
Stephenson, Laura B., and Crête, Jean. 2011. Studying political behavior: A comparison of internet and telephone surveys. International Journal of Public Opinion Research 23: 24–55.Google Scholar
Traugott, Michael. 2012. Methodological trends and controversies in the media's use of opinion polls. In Opinion polls and the media: Reflecting and shaping public opinion, eds. Holtz-Bacha, Christina and Strömbäck, Jesper, 69–90. New York: Palgrave-Macmillan.Google Scholar
Traugott, Michael W., and Tucker, Clyde. 1984. Strategies for predicting whether a citizen will vote and estimation of electoral outcomes. Public Opinion Quarterly 48: 330–43.Google Scholar
Traugott, Michael. 2005. The accuracy of the national pre-election polls in the 2004 presidential election. Public Opinion Quarterly 69: 642–54.Google Scholar
Traugott, Michael W., and Wlezien, Christopher. 2009. The dynamics of poll performance during the 2008 presidential nomination contest. Public Opinion Quarterly 73: 866–94.Google Scholar
Visser, Penny S., Krosnick, Jon A., Marquette, Jesse, and Curtin, Michael. 1996. Mail surveys for election forecasting? An evaluation of the Columbus Dispatch poll. Public Opinion Quarterly 60: 181–227.Google Scholar
Voss, D. Stephen, Gelman, Andrew, and King, Gary. 1995. Pre-election survey methodology: Details from eight polling organizations, 1988 and 1992. Public Opinion Quarterly 59: 98–132.Google Scholar
Weisberg, Herbert F. 2005. The total survey error approach: A guide to the new science of survey research. Chicago: University of Chicago Press.Google Scholar
Yeager, David S., Krosnick, Jon, Chang, LinChiat, Javitz, Harold S., Levendusky, Matthew S., Simpser, Alberto, and Wang, Rui. 2011. Comparing the accuracy of RDD telephone surveys and internet surveys conducted with probability and non-probability samples. Public Opinion Quarterly 75: 709–47.Google Scholar
Supplementary material: PDF

Barber et al. supplementary material

Supplementary Material

Download Barber et al. supplementary material(PDF)
PDF 2.3 MB
Supplementary material: File

Barber et al. supplementary material

Supplementary Material

Download Barber et al. supplementary material(File)
File 3.2 MB