compute_tfce: Threshold-Free Cluster-Enhancement correction

In permuco: Permutation Tests for Regression, (Repeated Measures) ANOVA/ANCOVA and Comparison of Signals

Threshold-Free Cluster-Enhancement correction

Description

Compute the TFCE correction given a matrix a permuted statistical signals.

Usage

compute_tfce(distribution, alternative = "greater", E = 0.5, H = 1, ndh)

Arguments

distribution	A matrix of permuted statistical signal. The first row indicating the observed statistics.
alternative	A character string indicating the alternative hypothesis. Default is "greater". Choose between "greater", "less" or "two.sided".
E	A scalar that represent the extend parameter of the TFCE transformation. Default is E = 0.5.
H	A scalar that represent the height parameter of the TFCE transformation. Default is H = 1.
ndh	The number of terms in the approximation of the integral.

Details

The approximation of the TFCE integral starts from the minimal statistic (among the permuted statistic), not 0. Indeed, the value of the integral (from 0, to this minimal value) is the same for all time points, all permutations and does not need to be computed to get p-values.

See Also

Other multcomp: compute_clusterdepth_head(), compute_clusterdepth(), compute_clustermass(), compute_maxT(), compute_minP(), compute_stepdownmaxT(), compute_troendle()

permuco documentation built on Sept. 11, 2024, 8:31 p.m.