shinymrp

shinymrp-package

Dual interfaces, graphical and programmatic, designed for intuitive applications of Multilevel Regression and Poststratification (MRP). Users can apply the method to a variety of datasets, from electronic health records to sample survey data, through an end-to-end Bayesian data analysis workflow. The package provides robust tools for data cleaning, exploratory analysis, flexible model building, and insightful result visualization. For more details, see Si et al. (2020) <a href="https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2020002/article/00003-eng.pdf?st=iF1_Fbrh">https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2020002/article/00003-eng.pdf?st=iF1_Fbrh</a> and Si (2025) tools:::Rd_expr_doi("10.1214/24-STS932").

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Dual interfaces, graphical and programmatic, designed for
intuitive applications of Multilevel Regression and Poststratification (MRP).
Users can apply the method to a variety of datasets, from electronic health records
to sample survey data, through an end-to-end Bayesian data analysis workflow.
The package provides robust tools for data cleaning, exploratory analysis,
flexible model building, and insightful result visualization. For more details, see
Si et al. (2020) <https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2020002/article/00003-eng.pdf?st=iF1_Fbrh>
and Si (2025) <doi:10.1214/24-STS932>.

Toan Tran

Interface for Multilevel Regression and Poststratification

Jonah Gabry

Yajuan Si

shinymrp-package function

Maintainer: Toan Tran <a href="/link/trannttoan97%40gmail.com?package=shinymrp&version=0.10.0" data-mini-rdoc="shinymrp::trannttoan97@gmail.com">trannttoan97@gmail.com</a> [copyright holder]
Authors:<ul>
<li>Jonah Gabry <a href="/link/jgabry%40gmail.com?package=shinymrp&version=0.10.0" data-mini-rdoc="shinymrp::jgabry@gmail.com">jgabry@gmail.com</a> [copyright holder]</li>
<li>Yajuan Si <a href="/link/yajuan%40umich.edu?package=shinymrp&version=0.10.0" data-mini-rdoc="shinymrp::yajuan@umich.edu">yajuan@umich.edu</a> [copyright holder]</li>
</ul>

Author

Dual interfaces, graphical and programmatic, designed for intuitive applications of Multilevel Regression and Poststratification (MRP). Users can apply the method to a variety of datasets, from electronic health records to sample survey data, through an end-to-end Bayesian data analysis workflow. The package provides robust tools for data cleaning, exploratory analysis, flexible model building, and insightful result visualization. For more details, see Si et al. (2020) <a href='https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2020002/article/00003-eng.pdf?st=iF1_Fbrh'>https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2020002/article/00003-eng.pdf?st=iF1_Fbrh</a> and Si (2025) tools:::Rd_expr_doi("10.1214/24-STS932").

shinymrp: Interface for Multilevel Regression and Poststratification — shinymrp-package

Maintainer: Toan Tran <a href='mailto:trannttoan97@gmail.com'>trannttoan97@gmail.com</a> [copyright holder]
Authors:<ul>
<li>Jonah Gabry <a href='mailto:jgabry@gmail.com'>jgabry@gmail.com</a> [copyright holder]</li>
<li>Yajuan Si <a href='mailto:yajuan@umich.edu'>yajuan@umich.edu</a> [copyright holder]</li>
</ul>

shinymrp-package: shinymrp: Interface for Multilevel Regression and Poststratification

Description

Arguments

Author

See Also