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Post-Stratification without Population Level Information on the Post-Stratifying Variable, with Application to Political Polling

Author

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  • Reilly, Cavan
  • Gelman, Andrew
  • Katz, Jonathan N.

Abstract

We investigate the construction of more precise estimates of a collection of population means using information about a related variable in the context of repeated sample surveys. The method is illustrated using poll results concerning presidential approval rating (our related variable is political party identification). We use post-stratification to construct these improved estimates, but since we don't have population level information on the post-stratifying variable, we construct a model for the manner in which the post-stratifier develops over time. In this manner, we obtain more precise estimates without making possibly untenable assumptions about the dynamics of our variable of interest, the presidential approval rating.

Suggested Citation

  • Reilly, Cavan & Gelman, Andrew & Katz, Jonathan N., 2000. "Post-Stratification without Population Level Information on the Post-Stratifying Variable, with Application to Political Polling," Working Papers 1091, California Institute of Technology, Division of the Humanities and Social Sciences.
    • Handle: RePEc:clt:sswopa:1091
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    File URL: http://www.hss.caltech.edu/SSPapers/wp1091.pdf
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    Cited by:

    1. Martin Andrew D. & Hazelton Morgan L.W., 2012. "What Political Science Can Contribute to the Study of Law," Review of Law & Economics, De Gruyter, vol. 8(2), pages 511-529, October.
    2. Wang, Wei & Rothschild, David & Goel, Sharad & Gelman, Andrew, 2015. "Forecasting elections with non-representative polls," International Journal of Forecasting, Elsevier, vol. 31(3), pages 980-991.
    3. Maciej Beręsewicz, 2017. "A Two-Step Procedure to Measure Representativeness of Internet Data Sources," International Statistical Review, International Statistical Institute, vol. 85(3), pages 473-493, December.

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