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Computing quantities of interest and their uncertainty using Bayesian simulation
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Murr, Andreas, Traunmüller, Richard and Gill, Jeff (2022) Computing quantities of interest and their uncertainty using Bayesian simulation. Political Science Research and Methods . doi:10.1017/psrm.2022.18 ISSN 2049-8470. (In Press)
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Official URL: http://dx.doi.org/10.1017/psrm.2022.18
Abstract
When analyzing data, researchers are often less interested in the parameters of statistical models than in functions of these parameters such as predicted values. Here we show that Bayesian simulation with Markov-chain Monte Carlo tools makes it easy to compute these quantities of interest with their uncertainty. We illustrate how to produce customary and relatively new quantities of interest such as variable importance ranking, posterior predictive data, difficult marginal effects, and model comparison statistics to allow researchers to report more informative results.
| Item Type: | Journal Article | ||||||
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| Subjects: | H Social Sciences > H Social Sciences (General) H Social Sciences > HA Statistics Q Science > QA Mathematics |
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| Divisions: | Faculty of Social Sciences > Politics and International Studies | ||||||
| Library of Congress Subject Headings (LCSH): | Quantitative research, Quantitative research -- Statistical methods, Statistics , Bayesian statistical decision theory | ||||||
| Journal or Publication Title: | Political Science Research and Methods | ||||||
| Publisher: | Cambridge University Press | ||||||
| ISSN: | 2049-8470 | ||||||
| Official Date: | 26 April 2022 | ||||||
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| DOI: | 10.1017/psrm.2022.18 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | In Press | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Date of first compliant deposit: | 2 March 2022 | ||||||
| Date of first compliant Open Access: | 2 March 2022 | ||||||
| RIOXX Funder/Project Grant: |
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