Determine sample size with the Bayesian Interval Equivalence Method

Script for pre-calculation. The present method provides an expected sample size such that compelling evidence in the form of a Bayes factor can be collected for a given eq band with a certain long-run probability.

Usage

ssp_anova_eq(
  mu,
  effect,
  eq_band,
  tpr,
  thresh,
  prior_scale,
  iter,
  post_iter = 1000,
  sigma = 1,
  prior_location = 0,
  max_n = 10001,
  seed = NULL
)

twoway_ANOVA_eq_pwr(
  n = n1,
  effect = effect,
  eq_band = eq_band,
  iter = iter,
  post_iter = post_iter,
  mu = mu,
  sigma = sigma,
  thresh = thresh,
  prior_scale = prior_scale,
  prior_location = prior_location,
  seed = NULL
)

Arguments

mu: Numeric. The unstandardized mean of the DV for each group.
effect: Character. The effect of interest (main effect A, main effect B).
eq_band: Numeric. The margin of the standardized equivalence region.
tpr: Numeric. The desired long-run probability of obtaining a Bayes factor higher than Thresh, given the means.
thresh: Numeric. The threshold of the Bayes Factor which is fixed to 10 in the ShinyApp.
prior_scale: Numeric. The scale of the Cauchy prior which is fixed to 1 / sqrt(2) in the ShinyApp.
iter: Numeric. The number of iterations to calculate the TPR which is fixed to 1000 in the ShinyApp.
post_iter: Numeric. The number of iterations to estimate the posterior distribution which is fixed to 1000 in the ShinyApp.
sigma: Numeric. The standard deviation of the DV for the groups.
prior_location: Numeric. The scale of the Cauchy prior which is fixed to 1 / sqrt(2) in the ShinyApp.
max_n: Numeric. The maximum group size which is fixed to 500 in the ShinyApp.
seed: Numeric. Seed for the random calculations.
n: Numeric. The sample size per group during the tpr optimization process.

Value

The function returns a list of two named numeric vectors. The second `n1` the determined sample size per group. The third `tpr_out` is the TPR corresponding to the determined sample sizes.