Simulate two-condition time-course data for cluster-permutation examples — simulate_gazepoint_cluster_timecourse

Creates participant-level synthetic time-course data with an optional effect window. The function is intended for examples, tests, teaching, and documentation.

Usage

simulate_gazepoint_cluster_timecourse_data(
  n_subjects = 12L,
  n_time = 60L,
  conditions = c("A", "B"),
  effect_start = 25,
  effect_end = 38,
  effect_size = 0.6,
  noise_sd = 0.4,
  subject_sd = 0.25,
  time_start = 1,
  time_step = 1,
  effect_condition = "B",
  seed = NULL
)

Arguments

n_subjects: Number of participants.
n_time: Number of time bins.
conditions: Character vector of two condition labels.
effect_start: First time value included in the effect window.
effect_end: Last time value included in the effect window.
effect_size: Additive effect size inside the effect window.
noise_sd: Standard deviation of observation-level noise.
subject_sd: Standard deviation of participant-level random intercepts.
time_start: First time value.
time_step: Step between time bins.
effect_condition: Condition receiving the additive effect.
seed: Optional random seed.

Value

A data frame with columns subject, condition, time, value, and true_effect.