example_sample_data

Return example data based on the specified characteristics.

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

example_sample_data function

<dl><dt>is_timevar</dt>
<dd>Logical indicating whether the data is time-varying.</dd>
<dt>is_aggregated</dt>
<dd>Logical indicating whether the data is aggregated.</dd>
<dt>special_case</dt>
<dd>Optional character string for specific use cases such as COVID data.
Options are <code>NULL</code>, <code>"covid"</code> and <code>"poll"</code>. The default is <code>NULL</code> which indicates the
data is not specific to any supported use case.</dd>
<dt>family</dt>
<dd>Character string specifying the distribution family for outcome measures.
Options are <code>"binomial"</code> for binary outcomes and <code>"normal"</code> for continuous outcomes.</dd></dl>

Arguments

Return example data — example_sample_data

<dl>

<dt>is_timevar</dt>
<dd>Logical indicating whether the data is time-varying.</dd>


<dt>is_aggregated</dt>
<dd>Logical indicating whether the data is aggregated.</dd>


<dt>special_case</dt>
<dd>Optional character string for specific use cases such as COVID data.
Options are <code>NULL</code>, <code>"covid"</code> and <code>"poll"</code>. The default is <code>NULL</code> which indicates the
data is not specific to any supported use case.</dd>


<dt>family</dt>
<dd>Character string specifying the distribution family for outcome measures.
Options are <code>"binomial"</code> for binary outcomes and <code>"normal"</code> for continuous outcomes.</dd>

</dl>

example_sample_data: Return example data

Description

Usage

Value

Arguments