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An Approximation of Joint Distributions of Weighting Variables Using a Pseudo Population Approach

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  • Bruch, Christian
  • Felderer, Barbara

Abstract

Several weighting techniques require joint distributions of weighting variables on a population level in order to adjust for the selectivity in the participation process of the survey. In practical applications, joint distributions are frequently not available and population margins are the only information available to inform the weighting procedure. We propose a novel approach to estimate the population sizes of weighting cells based on a pseudo population that was constructed using a copula. The approach makes use of population margins of weighting variables and their correlations. We show how the approach can be used for poststratification and multilevel regression and poststratification approaches and illustrate the usefulness in a simulation study and an empirical example. Using the copula pseudo population approach in combination with multilevel regression and poststratification for highly selective data strongly improves the survey estimation as compared to traditional raking and poststratification methods in our study.

Suggested Citation

  • Bruch, Christian & Felderer, Barbara, 2024. "An Approximation of Joint Distributions of Weighting Variables Using a Pseudo Population Approach," OSF Preprints pg2wt, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:pg2wt
    DOI: 10.31219/osf.io/pg2wt
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    5. 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.
    6. S Chen & D Haziza & C Léger & Z Mashreghi, 2019. "Pseudo-population bootstrap methods for imputed survey data," Biometrika, Biometrika Trust, vol. 106(2), pages 369-384.
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