data_lnln: Simulation Data for Lognormal-Lognormal Model
In hbsaems: Hierarchical Bayes Small Area Estimation Model using 'Stan'

data_lnln

R Documentation

Simulation Data for Lognormal-Lognormal Model

Description

This dataset is a simulated data created for demonstrating the implementation of Hierarchical Bayesian Small Area Estimation (HB SAE) using a lognormal-lognormal model. It includes area-level covariates, random effects, direct estimates, and spatial components, for testing SAE models with lognormal assumptions and spatial correlation.

Usage

data_lnln

Format

A data frame with 100 rows and 13 variables:

group: Area ID (1–100) for random effects formula specifying the grouping structure in the data.
x1, x2, x3: Auxiliary area-level covariates
u_true: True unstructured area-level random effect on the log scale.
teta_true: True linear predictor on the log scale (meanlog for lognormal distribution).
mu_orig_true: True mean on the original scale, calculated from eta_true and sigma_e.
n: Sample size per area.
y_obs: Simulated observed mean per area, generated from a lognormal distribution.
lambda_dir: Direct estimator of the mean per area (same as y_obs).
y_log_obs: Log-transformed direct estimator.
psi_i: Approximate sampling variance of y_obs.
sre: An optional grouping factor mapping observations to spatial locations.