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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 

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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.

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Supplementary material: PDF

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