Advanced simulation framework for test validation¶

Source: R/simulation_framework.R · Help: ?simulation_framework

Provides tools for validating heteroscedasticity tests under controlled scenarios and estimating statistical power.

simulate_type_I_errors() and simulate_power_analysis() are deprecated since 0.14.0: use simulate_size() and simulate_power(), which return the same results and belong to the documented snake_case family of simulate_*() and sigma_*() functions. The old names still work and warn.

Usage¶

simulate_size(
  test_function,
  n_sims = 1000,
  alpha = 0.05,
  n_obs = 100,
  seed = 123
)

simulate_power(
  test_function,
  sigma_functions = list(sigma_linear),
  effect_sizes = c(0.1, 0.2, 0.5, 1),
  n_sims = 500,
  n_obs = 100,
  alpha = 0.05
)

simulate_type_I_errors(
  test_function,
  n_sims = 1000,
  alpha = 0.05,
  n_obs = 100,
  seed = 123
)

simulate_power_analysis(
  test_function,
  sigma_functions = list(sigma_linear),
  effect_sizes = c(0.1, 0.2, 0.5, 1),
  n_sims = 500,
  n_obs = 100,
  alpha = 0.05
)

Arguments¶

test_function: Function taking a model and data and returning an object with a numeric p.value component.
n_sims: Number of simulation replications.
alpha: Significance level for Type I error or power calculations.
n_obs: Number of observations for generated datasets.
seed: Optional integer seed for reproducibility.
sigma_functions: List of variance functions generating heteroscedastic patterns.
effect_sizes: Numeric vector of effect size multipliers.

Value¶

A list summarising Type I error rate or a data frame of power estimates.