Prior Choice for the Variance Parameter in the Multilevel Regression and Poststratification Approach for Highly Selective Data. A Monte Carlo Simulation Study.
The multilevel and poststratification approach is commonly used to draw valid inference from (non-probabilistic) surveys. This Bayesian approach includes varying regression coefficients for which prior distributions of their variance parameter must be specified. The choice of the distribution is fa...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Austrian Statistical Society
2022-08-01
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| Series: | Austrian Journal of Statistics |
| Online Access: | https://www.ajs.or.at/index.php/ajs/article/view/1361 |
| _version_ | 1828121273279971328 |
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| author | Christian Bruch Barbara Felderer |
| author_facet | Christian Bruch Barbara Felderer |
| author_sort | Christian Bruch |
| collection | DOAJ |
| description |
The multilevel and poststratification approach is commonly used to draw valid inference from (non-probabilistic) surveys. This Bayesian approach includes varying regression coefficients for which prior distributions of their variance parameter must be specified. The choice of the distribution is far from being trivial and many contradicting recommendations exist in the literature. The prior choice may be even more challenging when data results from a highly selective inclusion mechanism, such as applied by volunteer panels. We conduct a Monte Carlo simulation study to evaluate the effect of different distribution choices on bias in the estimation of a proportion based on a sample that is subject to a highly selective inclusion mechanism.
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| first_indexed | 2024-04-11T14:18:26Z |
| format | Article |
| id | doaj.art-f662dd0a11d44717b4189b88199edfad |
| institution | Directory Open Access Journal |
| issn | 1026-597X |
| language | English |
| last_indexed | 2024-04-11T14:18:26Z |
| publishDate | 2022-08-01 |
| publisher | Austrian Statistical Society |
| record_format | Article |
| series | Austrian Journal of Statistics |
| spelling | doaj.art-f662dd0a11d44717b4189b88199edfad2022-12-22T04:19:09ZengAustrian Statistical SocietyAustrian Journal of Statistics1026-597X2022-08-0151410.17713/ajs.v51i4.1361Prior Choice for the Variance Parameter in the Multilevel Regression and Poststratification Approach for Highly Selective Data. A Monte Carlo Simulation Study.Christian Bruch0Barbara Felderer1GESIS Leibniz Institute for the Social SciencesGESIS Leibniz Institute for the Social Sciences The multilevel and poststratification approach is commonly used to draw valid inference from (non-probabilistic) surveys. This Bayesian approach includes varying regression coefficients for which prior distributions of their variance parameter must be specified. The choice of the distribution is far from being trivial and many contradicting recommendations exist in the literature. The prior choice may be even more challenging when data results from a highly selective inclusion mechanism, such as applied by volunteer panels. We conduct a Monte Carlo simulation study to evaluate the effect of different distribution choices on bias in the estimation of a proportion based on a sample that is subject to a highly selective inclusion mechanism. https://www.ajs.or.at/index.php/ajs/article/view/1361 |
| spellingShingle | Christian Bruch Barbara Felderer Prior Choice for the Variance Parameter in the Multilevel Regression and Poststratification Approach for Highly Selective Data. A Monte Carlo Simulation Study. Austrian Journal of Statistics |
| title | Prior Choice for the Variance Parameter in the Multilevel Regression and Poststratification Approach for Highly Selective Data. A Monte Carlo Simulation Study. |
| title_full | Prior Choice for the Variance Parameter in the Multilevel Regression and Poststratification Approach for Highly Selective Data. A Monte Carlo Simulation Study. |
| title_fullStr | Prior Choice for the Variance Parameter in the Multilevel Regression and Poststratification Approach for Highly Selective Data. A Monte Carlo Simulation Study. |
| title_full_unstemmed | Prior Choice for the Variance Parameter in the Multilevel Regression and Poststratification Approach for Highly Selective Data. A Monte Carlo Simulation Study. |
| title_short | Prior Choice for the Variance Parameter in the Multilevel Regression and Poststratification Approach for Highly Selective Data. A Monte Carlo Simulation Study. |
| title_sort | prior choice for the variance parameter in the multilevel regression and poststratification approach for highly selective data a monte carlo simulation study |
| url | https://www.ajs.or.at/index.php/ajs/article/view/1361 |
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