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      Bayesian Multilevel Estimation with Poststratification: State-Level Estimates from National Polls

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      Political Analysis

      Oxford University Press (OUP)

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          Abstract

          We fit a multilevel logistic regression model for the mean of a binary response variable conditional on poststratification cells. This approach combines the modeling approach often used in small-area estimation with the population information used in poststratification (see Gelman and Little 1997, Survey Methodology 23:127–135). To validate the method, we apply it to U.S. preelection polls for 1988 and 1992, poststratified by state, region, and the usual demographic variables. We evaluate the model by comparing it to state-level election outcomes. The multilevel model outperforms more commonly used models in political science. We envision the most important usage of this method to be not forecasting elections but estimating public opinion on a variety of issues at the state level.

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          Measuring Citizen and Government Ideology in the American States, 1960-93

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            Why Are American Presidential Election Campaign Polls So Variable When Votes Are So Predictable?

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              Public Opinion in the American States: New Perspectives Using National Survey Data

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                Author and article information

                Journal
                applab
                Political Analysis
                Polit. anal.
                Oxford University Press (OUP)
                1047-1987
                1476-4989
                2004
                January 2017
                : 12
                : 04
                : 375-385
                Article
                10.1093/pan/mph024
                © 2004

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