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

Cavan Reilly Cavan Reilly is Assistant Professor, Department of Biostatistics, University of Minnesota, Minneapolis, MN 55454. Andrew Gelman is Professor, Department of Statistics, at Columbia University, New York, NY 10027 . Jonathan Katz is Associate Professor of Political Science, D.H.S.S., California Institute of Technology, Pasadena, CA 91125 . C. Reilly and A. Gelman thank the NSF for grant SBR-97-08424 and Young Investigator Award DMS-97-96129, and J. Katz thanks the John M. Olin Foundation.

Andrew Gelman Cavan Reilly is Assistant Professor, Department of Biostatistics, University of Minnesota, Minneapolis, MN 55454. Andrew Gelman is Professor, Department of Statistics, at Columbia University, New York, NY 10027 . Jonathan Katz is Associate Professor of Political Science, D.H.S.S., California Institute of Technology, Pasadena, CA 91125 . C. Reilly and A. Gelman thank the NSF for grant SBR-97-08424 and Young Investigator Award DMS-97-96129, and J. Katz thanks the John M. Olin Foundation.

Jonathan Katz Cavan Reilly is Assistant Professor, Department of Biostatistics, University of Minnesota, Minneapolis, MN 55454. Andrew Gelman is Professor, Department of Statistics, at Columbia University, New York, NY 10027 . Jonathan Katz is Associate Professor of Political Science, D.H.S.S., California Institute of Technology, Pasadena, CA 91125 . C. Reilly and A. Gelman thank the NSF for grant SBR-97-08424 and Young Investigator Award DMS-97-96129, and J. Katz thanks the John M. Olin Foundation.

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 poststratification to construct these improved estimates, but because we do not have population level information on the poststratifying variable, we construct a model for the manner in which the poststratifier 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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Poststratification Without Population Level Information on the Poststratifying Variable With Application to Political Polling

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

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