Hostname: page-component-84b7d79bbc-fnpn6 Total loading time: 0 Render date: 2024-07-28T14:35:02.573Z Has data issue: false hasContentIssue false

Exploring the Performance of Multilevel Modeling and Poststratification with Eurobarometer Data

Published online by Cambridge University Press:  04 January 2017

Dimiter Toshkov*
Affiliation:
Department of Public Administration, Leiden University, Schouwburgstraat 2, 2511VA The Hague, The Netherlands

Abstract

This text reports the results of an evaluation of the performance of multilevel regression modeling and poststratication (MRP) in reconstructing state-level estimates from federal-level data. The evaluation makes use of Eurobarometer data and relies on the fact that Eurobarometer provides representative survey data for each European Union state to further explore the performance of MRP. I repeatedly draw subsets of the entire Eurobarometer sample, then I compute adjusted country means using MRP with census data, and I compare the resulting estimates to the true country means from the full sample. I do that for ten survey items from various Eurobarometer waves. The results show that MRP is generally successful in producing estimates that are highly correlated with the true values (mean of 0.90). But the approach is less capable of reconstructing the relative rankings of the country means and hitting the range of plausible values of the individual state means. I also show that the great part of the adjustment comes from the modeling of the state means and not from poststratification, and that population-weighted samples perform no worse than samples in which countries have equal shares of the pool of respondents.

Type
Letters
Copyright
Copyright © The Author 2015. 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: Supplementary Materials for this article, including a more detailed presentation of the approach and additional results, are available on the Political Analysis Web site and the Web site of the author at http://www.dimiter.eu. Replication files are available on the Political Analysis Dataverse at http://dx.doi.org/10.7910/DVN/29488.

References

Buttice, Matthew K., and Highton, Benjamin. 2013. How does multilevel regression and poststratification perform with conventional national surveys? Political Analysis 21:449–67.Google Scholar
Canes-Wrone, Brandice, Clark, Tom S., and Kelly, J. P. 2014. Judicial selection and death penalty decisions. American Political Science Review 108:2339.Google Scholar
Gelman, Andrew, and Hill, Jennifer. 2007. Data analysis using regression and multilevel/hierarchical models. Cambridge, UK: Cambridge University Press.Google Scholar
Gehnan, Andrew, and Little, Thomas. 1997. Poststratification into many categories using hierarchical logistic regression. Survey Methodologist 23:127–35.Google Scholar
Kastellec, Jonathan P., Lax, Jeffrey R., and Phillips, Justin H. 2014. Estimating state public opinion with multi-level regression and poststratication using R. http://www.princeton.edu/∼jkastell/MRP_primer/mrp_primer.pdf.Google Scholar
Kastellec, Jonathan P., Lax, Jeffrey R., and Phillips, Justin H. 2010. Public opinion and senate confirmation of Supreme Court nominees. Journal of Politics 72:767–84.Google Scholar
Lax, Jeffrey R., and Phillips, Justin H. 2012. The democratic deficit in the states. American Journal of Political Science 56:148–66.CrossRefGoogle Scholar
Lax, Jeffrey R., and Phillips, Justin H. 2009. How should we estimate public opinion in the states? American Journal of Political Science 53:107–21.CrossRefGoogle Scholar
Pacheco, Julianna. 2011. Using national surveys to measure dynamic U.S. state public opinion: A guideline for scholars and an application. State Politics & Policy Quarterly 11:415–39.CrossRefGoogle 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.CrossRefGoogle Scholar
Stollwerk, Alissa. 2013. The application of multilevel regression with post-stratication to cluster sampled polls: Challenges and suggestions. http://www.uiowa.edu/∼stpols13/papers/Stollwerk_SPP_2013.pdf.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.CrossRefGoogle Scholar
Supplementary material: PDF

Toshkov supplementary material

Supplementary Material

Download Toshkov supplementary material(PDF)
PDF 898.1 KB