https://mrp-interface.r-universe.devRecent package updates in mrp-interfaceR-universehttps://github.com/mrp-interface.pnghttps://mrp-interface.r-universe.devThu, 04 Dec 2025 15:30:10 GMTtrannttoan97@gmail.com (Toan Tran)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>.https://github.com/r-universe/mrp-interface/actions/runs/38542470244Thu, 04 Dec 2025 15:30:10 GMTshinymrp0.10.0successhttps://mrp-interface.r-universe.devhttps://github.com/mrp-interface/shinymrpgetting-started.Rmdgetting-started.htmlGetting started with shinymrp2025-06-26 23:11:332025-10-06 17:42:36example.Rmdexample.htmlMore examples of R6 classes2025-09-18 05:42:272025-11-11 22:26:11data-prep.Rmddata-prep.htmlMore on data preparation2025-07-18 18:58:382025-11-24 23:38:55method.Rmdmethod.htmlMRP methodological guide2025-10-03 18:39:102025-10-06 19:04:42workflow.Rmdworkflow.htmlProgrammatic workflow demonstration2025-07-18 09:55:502025-12-01 06:23:21spatial-prior.Rmdspatial-prior.htmlSpatial prior specification in shinymrp2025-12-04 09:30:352025-12-04 09:30:35