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How Does Multilevel Regression and Poststratification Perform with Conventional National Surveys?

Published online by Cambridge University Press:  04 January 2017

Matthew K. Buttice  and
Benjamin Highton
Matthew K. Buttice
Affiliation:
California Research Bureau, California State Library, Sacramento, CA 94237-0001 e-mail: [email protected]
Benjamin Highton*
Affiliation:
Department of Political Science, University of California, Davis, CA 95616-8682
*
e-mail: [email protected] (corresponding author)
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Abstract

Multilevel regression and poststratification (MRP) is a method to estimate public opinion across geographic units from individual-level survey data. If it works with samples the size of typical national surveys, then MRP offers the possibility of analyzing many political phenomena previously believed to be outside the bounds of systematic empirical inquiry. Initial investigations of its performance with conventional national samples produce generally optimistic assessments. This article examines a larger number of cases and a greater range of opinions than in previous studies and finds substantial variation in MRP performance. Through empirical and Monte Carlo analyses, we develop an explanation for this variation. The findings suggest that the conditions necessary for MRP to perform well will not always be met. Thus, we draw a less optimistic conclusion than previous studies do regarding the use of MRP with samples of the size found in typical national surveys.

Type
Research Article
Information
Political Analysis , Volume 21 , Issue 4 , Autumn 2013 , pp. 449 - 467
Copyright
Copyright © The Author 2013. Published by Oxford University Press on behalf of the Society for Political Methodology 

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Footnotes

Authors' note: We appreciate helpful advice from Kyle Joyce, Eric McGhee, Matt Pietryka, and Walt Stone on this article. Buttice began work on this project while at UC Davis and finished while at the California Research Bureau. The research results and conclusions expressed in this article do not necessarily reflect the views of the California Research Bureau or California State Library. The replication archive for this article is available at the Political Analysis Dataverse as Buttice and Highton (2013). Supplementary materials for this article are available on the Political Analysis Web site.

References

Arceneaux, Kevin. 2001. The “gender gap” in state legislative representation: New data to tackle an old question. Political Research Quarterly 54: 143–60.Google Scholar
Berkman, Michael B., and Plutzer, Eric. 2005. Ten thousand democracies: Politics and public opinion in America's school districts. Washington, DC: Georgetown University Press.Google Scholar
Buttice, Matthew K., and Highton, Benajmin. 2013. Replication data for: How does multilevel regression and poststratification (MRP) perform with conventional national surveys? Dataverse Network. http://hdl.handle.net/1902.1/22001 (accessed September 17, 2013).Google Scholar
Erikson, Robert S., Wright, Gerald C., and McIver, John P. 1993. Statehouse democracy. New York, NY: Cambridge University Press.Google Scholar
Erikson, Robert S. 2006. Constituency influence in Congress. American Political Science Review 100: 674–4.Google Scholar
Gelman, Andrew, and Little, Thomas C. 1997. Poststratification into many categories using hierarchical logistic regression. Survey Methodology 23: 127–35.Google Scholar
Gelman, Andrew, and Hill, Jennifer. 2007. Data analysis using regression and multilevel/hierarchical models. New York, NY: Cambridge University Press.Google Scholar
Kastellec, Jonathan P., Lax, Jeffrey R., and Phillips, Justin H. 2010a. Estimating state public opinion with multi-level regression and poststratification using R. Unpublished manuscript, Princeton University.Google Scholar
Kastellec, Jonathan P., Lax, Jeffrey R., and Phillips, Justin H. 2010b. Public opinion and senate confirmation of Supreme Court nominees. Journal of Politics 72: 767–84.Google Scholar
Lax, Jeffrey R., and Phillips, Justin H. 2009a. Gay rights in the states: Public opinion and policy responsiveness. American Political Science Review 103: 367–86.Google Scholar
Lax, Jeffrey R., and Phillips, Justin H. 2009b. How should we estimate public opinion in the states? American Journal of Political Science 53: 107–21.Google Scholar
Lax, Jeffrey R., and Phillips, Justin H. 2012. The democratic deficit in the states. American Journal of Political Science 56: 148–66.Google Scholar
Miller, Warren E., and Stokes, Donald E. 1963. Constituency influence in Congress. American Political Science Review 57: 45–56.Google Scholar
Pacheco, Julianna. 2011. Using national surveys to measure dynamic U.S. state public opinion: A guideline for scholars and an application. State Politics and Policy Quarterly 11: 415–39.Google Scholar
Park, David K., Gelman, Andrew, and Bafumi, Joseph. 2004. Bayesian multilevel estimation with poststratification: State-level estimates from national polls. Political Analysis 12: 375–85.Google Scholar
Park, David K., Gelman, Andrew, and Bafumi, Joseph. 2006. State-level opinions from national surveys: Poststratification using multilevel logistic regression. In Public opinion in state politics, ed. Cohen, J. E. Palo Alto, CA: Stanford University Press.Google Scholar
Selb, Peter, and Munzert, Simon. 2011. Estimating constituency preferences from sparse survey data using auxiliary geographic information. Political Analysis 19: 455–70.Google Scholar
Shapiro, Robert Y. 2011. Public opinion and American democracy. Public Opinion Quarterly 75: 982–1017.Google Scholar
Warshaw, Christopher, and Rodden, Jonathan. 2012. How should we measure district-level public opinion on individual issues? Journal of Politics 74: 203–19.Google Scholar