perm4PTCA: 'perm4PTCA' Permutation test for the inertia and eigenvalues...

In HerveAbdi/PTCA4CATA: Partial Triadic Analysis (PTCA) for Check All That Apply (CATA) Data

perm4PTCA Permutation test for the inertia and eigenvalues for PTCA

Description

perm4PTCA Permutation for PTCA4CATA. Computes an omnibus permutation test and specific tests for the eigenvalues when performing a PTCA analysis on Check All That Apply (CATA) Data. Input is a Cube of data (products*Descriptors*Assessors). Three different permutation schemes are currently available (see paramater permType).

Usage

perm4PTCA(
  aCube,
  nIter = 1000,
  permType = "byRows",
  compact = FALSE,
  Malinvaud = TRUE
)

Arguments

aCube	an I*J*K (i.e., products*Descriptors*Assessors) of CATA Data.
nIter	(Default = 1000). Number of Iterations (i.e., number of permuted samples computed).
permType	what type of permutation is used if 'byRows' (default) the data are permuted within the rows (i.e., products) for each assessor. if 'byCols' the data are permuted within the columns (i.e., descriptors) for each assessor. if 'byMat' the data are permuted within the whole data matrix (i.e., products*descriptors) for each assessor.
compact	if TRUE return (Default) only p-values for omnibus test
Malinvaud	(default = TRUE) return the results of the Malinvaud-Saporta chi square test

Value

a list with fixedInertia: the CA-inertia of the data matrix; fixedEigenvalues: the CA-eigenvalues of the data matrix; pOmnibus: the probability associated to the inertia. If compact is FALSE, return also permInertia: an nIter * 1 vector containing the permutated inertia; pEigenvalues: The probabilites associated to each eigenvalue; If compact is is FALSE, return also permEigenvalues: an nIter * L matrix giving the permuted eigenvalues.

Author(s)

Herve Abdi

HerveAbdi/PTCA4CATA documentation built on July 17, 2022, 5:41 a.m.