Determine sample size with the Classical power analysis method — ssp_power_traditional

This method is used to estimate the minimum sample size that a design needs to reach a statistical power, given a desired significance level and expected effect size.

Usage

ssp_power_traditional_anova(
  effect = c("Main Effect A", "Main Effect B", "Interaction Effect"),
  iter = 1000,
  max_n,
  mu,
  sigma,
  seed = NULL,
  tpr,
  alpha = 0.05
)

Arguments

effect: Character. The effect of interest (main effect A, main effect B, interaction effect).
iter: Integer. The number of iterations.
max_n: Integer. The maximum number of participants per group (both groups are assumed to have equal sample size).
mu: Numeric. The mean of the DV for each group.
sigma: Numeric. The standard deviation of the DV for the groups.
seed: Numeric. The seed for reproducibility.
tpr: Numeric. The desired long-run probability of obtaining a significant result, given the means.
alpha: Numeric. The level of significance.

Value

The function returns a list of one named numeric vector. The vector called `n1` contains the determined sample size per group for the given design.

Examples

if (FALSE) { # \dontrun{
SampleSizePlanner::ssp_power_traditional_anova(
  tpr = 0.8, max_n = 400, mu = c(1, 1.2, 1.5, 1.3), sigma = 2,
  seed = NULL, alpha = 0.05
 )
} # }