Functions to compute p-values based on permutation tests. Regression, ANOVA and ANCOVA, omnibus F-tests, marginal unilateral and bilateral t-tests are available. Several methods to handle nuisance variables are implemented (Kherad-Pajouh, S., & Renaud, O. (2010)
This package provides functions to compute permutation tests in linear models with nuisances variables. The package has several goals :
lmperm()
functionThis function is constructed as an extension of the the lm()
function for permutation test. It produces t statistics with univariate and bivariate p-value by permutation.
aovperm()
functionThis function is constructed as an extension of the the aov()
function for permutation test. It produces marginal F statistics (type III) for factorial ANOVA and ANCOVA. Moreover, repeated measures ANOVA can be perform using the same notations used in an aov()
formula with +Error(id/within)
to specify the random effects.
clusterlm()
functionThis function compute cluster-mass statistics for multiple comparisons. It is designed for ERP analysis of unichannel EEG data. The left part of formula object must be a matrix or dataframe which columns represents multiple responses tested on the same experimental design (specified by right part of the formula). This function provides several methods to handle nuisance variables, a F or t statistics, an extension for repeated measure anova and several methods for the multiple comparisons lit the threshold-free cluster enhancement.
If you need help to use the package or want to report errors, contact Jaromil Frossard at [email protected].
For permutation tests with nuisance variables :
For permutation test in repeated measures ANOVA :
For cluster-mass statistics for the muliple comparison problems :
For the threshold-free cluster-enhancement method :
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