data_betalogitnorm

The <code>data_betalogitnorm</code> is a simulation data created specifically to demonstrate the implementation of
Hierarchical Bayesian Small Area Estimation (HB SAE) with Beta distribution.
This data is suitable for testing Beta regression models with a hierarchical structure
between areas. This data is also equipped with variables that apply spatial effects.

datasets

Implementing Hierarchical Bayesian Small Area Estimation
models using the 'brms' package as the computational backend. The
modeling framework follows the methodological foundations described in area-level
models. This package is designed to facilitate a principled Bayesian workflow,
enabling users to conduct prior predictive checks, model fitting, posterior
predictive checks, model comparison, and sensitivity analysis in a coherent and
reproducible manner. It supports flexible model specifications via 'brms' and
promotes transparency in model development, aligned with the recommendations of
modern Bayesian data analysis practices, implementing methods described in
Rao and Molina (2015) <doi:10.1002/9781118735855>.

Achmad Syahrul Choir

hbsaems

Hierarchical Bayes Small Area Estimation Model using 'Stan'

Saniyyah Sri Nurhayati

Sofi Zamzanah

Arsyka Laila Oktalia Siregar

data_betalogitnorm function

A data frame with 100 rows and 9 variables:<dl>
<dt>y</dt>
<dd>Response variable - The proportion of simulation results, has a value between 0 and 1, follows a Beta distribution.</dd><dt>theta</dt>
<dd>True latent mean parameter on the logit scale, representing the underlying probability of success in each area.</dd><dt>x1, x2, x3</dt>
<dd>Predictors Variables</dd><dt>n</dt>
<dd>The number of sample units for each region used in the survey</dd><dt>deff</dt>
<dd>Design Effect</dd><dt>group</dt>
<dd>Area ID (1–100) Random effects formula specifying the grouping structure in the data.</dd><dt>sre</dt>
<dd>An optional grouping factor mapping observations to spatial locations.</dd>
</dl>

Format

Simulation Data for Beta Logit Normal Model — data_betalogitnorm

A data frame with 100 rows and 9 variables:<dl>
<dt>y</dt>
<dd>Response variable - The proportion of simulation results, has a value between 0 and 1, follows a Beta distribution.</dd>

<dt>theta</dt>
<dd>True latent mean parameter on the logit scale, representing the underlying probability of success in each area.</dd>

<dt>x1, x2, x3</dt>
<dd>Predictors Variables</dd>

<dt>n</dt>
<dd>The number of sample units for each region used in the survey</dd>

<dt>deff</dt>
<dd>Design Effect</dd>

<dt>group</dt>
<dd>Area ID (1–100) Random effects formula specifying the grouping structure in the data.</dd>

<dt>sre</dt>
<dd>An optional grouping factor mapping observations to spatial locations.</dd>


</dl>

data_betalogitnorm: Simulation Data for Beta Logit Normal Model

Description

Usage

Arguments

Format

Examples