dot-auto_data_generator: Automatic Data Generator for brms + INLA Simulation...

In powerbrmsINLA: Bayesian Power Analysis Using 'brms' and 'INLA'

Automatic Data Generator for brms + INLA Simulation (Multi-Effect Ready)

Description

Creates a simulation function taking n (sample size) and a named effect vector/list. Supports multiple predictors, brms-style random effects, and most GLM families.

Usage

.auto_data_generator(
  formula,
  effect_name,
  family = gaussian(),
  family_args = list(),
  error_sd = 1,
  group_sd = 0.5,
  obs_per_group = 10,
  predictor_means = NULL,
  predictor_sds = NULL
)

Arguments

formula	Model formula (may include brms-style random effects).
effect_name	Character vector of fixed effect names to manipulate.
family	brms family object, e.g. gaussian(), binomial().
family_args	Named list of family-specific arguments.
error_sd	Residual SD for Gaussian-like families.
group_sd	SD of random effects.
obs_per_group	Number of observations per grouping level.
predictor_means	Named list of means for continuous predictors.
predictor_sds	Named list of SDs for continuous predictors.

Value

Function: function(n, effect) returns a data.frame with n rows.

powerbrmsINLA documentation built on July 2, 2026, 5:07 p.m.