.makePValueMat

the $3$-ways <code>array</code> containing the
 p-values for each pairwise comparison in each
 variable

the <code>character</code> string
 indicating which multiplicity correction must be used

multAdjMethod

<code>character</code> vector containing the
 groups' labels

groupsLabs

Take as input the $3$-ways array of p-values
 and return the $G x G x V$
 matrix of observed p-values adjusted for
 multiplicity; $G, V$ are, respectively, the number of
 groups/treatments and the number of variables.

Construct a ranking of a set of treatments/groups by
gathering together information coming from several response variables.
It can be used with both balanced and unbalanced experiments
(with almost all test statistics) as well as in presence of either
continuous covariates or a stratifying (categorical) variable.

.makePValueMat: Construct Univariate p-Values Matrix

Description

Usage

Arguments

Value