MRPWorkflow-method-preprocessed_data

preprocessed_data

<p>The <code>$preprocessed_data()</code> method returns the preprocessed sample data.
Check out the <a href="https://mrp-interface.github.io/shinymrp/articles/example#preprocessed_data">More examples of R6 classes</a>
vignette for usage examples.</p>

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

shinymrp

Interface for Multilevel Regression and Poststratification

Jonah Gabry

Yajuan Si

MRPWorkflow-method-preprocessed_data function

<p>The <code>$preprocessed_data()</code> method returns the preprocessed sample data.
Check out the <a href='https://mrp-interface.github.io/shinymrp/articles/example#preprocessed_data'>More examples of R6 classes</a>
vignette for usage examples.</p>

MRPWorkflow-method-preprocessed_data: Return preprocessed sample data

Description

Usage

Arguments

Value