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Poststratification Without Population Level Information on the Poststratifying Variable With Application to Political Polling

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  • Reilly C.
  • Gelman A.
  • Katz J.

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.
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  • Reilly C. & Gelman A. & Katz J., 2001. "Poststratification Without Population Level Information on the Poststratifying Variable With Application to Political Polling," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1-11, March.
    • Handle: RePEc:bes:jnlasa:v:96:y:2001:m:march:p:1-11
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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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