Functions for statistical analysis of physiological signal data, including t-tests, ANOVA, cluster-based permutation tests, and effect sizes. Pointwise t-test across epochs
Usage
tTestEpochs(
x,
condition1 = NULL,
condition2 = NULL,
mu = 0,
paired = FALSE,
alternative = c("two.sided", "less", "greater"),
var.equal = FALSE
)Arguments
- x
An epoched PhysioExperiment object (4D data).
- condition1
Indices or logical vector for first condition epochs.
- condition2
Indices or logical vector for second condition epochs. If NULL, performs one-sample t-test against mu.
- mu
Value to test against for one-sample t-test (default: 0).
- paired
Logical; if TRUE, performs paired t-test.
- alternative
Alternative hypothesis: "two.sided", "less", or "greater".
- var.equal
Logical; if TRUE, assumes equal variances.
Value
A list containing:
- t_values
Matrix of t-statistics (time x channel)
- p_values
Matrix of p-values (time x channel)
- df
Degrees of freedom
- n1, n2
Sample sizes for each condition
Details
Performs t-tests at each time point and channel, comparing epochs against a baseline or between two conditions.
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
anovaEpochs() for multi-group comparisons,
clusterPermutationTest() for multiple comparison correction,
effectSize() for Cohen's d effect size, correctPValues() for
p-value correction methods.
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
)
# One-sample t-test against zero
result <- tTestEpochs(pe)
# Two-sample t-test comparing conditions
result2 <- tTestEpochs(pe, condition1 = 1:10, condition2 = 11:20)