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

Cavan Reilly, Andrew Gelman and Jonathan Katz (jkatz@caltech.edu)

No 1091, Working Papers from California Institute of Technology, Division of the Humanities and Social Sciences

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.

Keywords: Bayesian inference; post-stratification; sample surveys; State-space models. (search for similar items in EconPapers)
Pages: 21 pages
Date: 2000-05
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Journal Article: Poststratification Without Population Level Information on the Poststratifying Variable With Application to Political Polling (2001)
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