Bootstrap confidence interval for ERP

Computes bootstrap confidence intervals for averaged epochs.

Usage

bootstrapCI(
  x,
  n_bootstrap = 1000L,
  ci_level = 0.95,
  condition = NULL,
  seed = NULL
)

Arguments

x

An epoched PhysioExperiment object (4D data).

n_bootstrap

Number of bootstrap iterations (default: 1000).

ci_level

Confidence interval level (default: 0.95).

condition

Epoch indices to include. If NULL, uses all epochs.

seed

Random seed for reproducibility.

Value

A list containing:

mean

Mean across epochs (time x channel)

ci_lower

Lower CI bound (time x channel)

ci_upper

Upper CI bound (time x channel)

se

Standard error (time x channel)

References

Maris, E. & Oostenveld, R. (2007). "Nonparametric statistical testing of EEG- and MEG-data." Journal of Neuroscience Methods, 164(1), 177-190. doi:10.1016/j.jneumeth.2007.03.024

See also

effectSize() for Cohen's d effect size, tTestEpochs() for parametric significance testing, plotERP() for ERP visualization.

Examples

# Create example epoched data
set.seed(123)
epochs <- array(rnorm(100 * 4 * 20 * 1), dim = c(100, 4, 20, 1))
pe <- PhysioExperiment(
  assays = list(epoched = epochs),
  samplingRate = 100
)
# Bootstrap CI
result <- bootstrapCI(pe, n_bootstrap = 500)