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Multilevel Regression and Poststratification in Stata

Author

Listed:
  • Maurizio Pisati

    (University of Milano-Bicocca
    Harvard School of Public Health)

  • Valeria Glorioso

    (University of Milano-Bicocca)

Abstract

Sometimes social scientists are interested in determining whether, and to what extent, the distribution of a given variable of interest Y varies across the categories of a second variable D. When the number of valid observations within one or more categories of D is small and/or collected data are affected by selection bias, relatively accurate estimates of E(Y|D) can be obtained by using a proper combination of multilevel regression modeling and poststratification, called the MrP approach (Gelman and Little 1997; Park, Gelman and Bafumi 2004; Lax and Phillips 2009). The purpose of this talk is to illustrate the main features and applications of -mrp-, a new user-written program that implements the MrP approach in Stata.

Suggested Citation

  • Maurizio Pisati & Valeria Glorioso, 2011. "Multilevel Regression and Poststratification in Stata," CHI11 Stata Conference 4, Stata Users Group.
    • Handle: RePEc:boc:chic11:4
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    File URL: http://fmwww.bc.edu/repec/chic2011/chi11_pisati.pdf
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    References listed on IDEAS

    as
    1. Lax, Jeffrey R. & Phillips, Justin H., 2009. "Gay Rights in the States: Public Opinion and Policy Responsiveness," American Political Science Review, Cambridge University Press, vol. 103(3), pages 367-386, August.
    2. Park, David K. & Gelman, Andrew & Bafumi, Joseph, 2004. "Bayesian Multilevel Estimation with Poststratification: State-Level Estimates from National Polls," Political Analysis, Cambridge University Press, vol. 12(4), pages 375-385.
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