Fg.test.pls

vector of the concatenate indipendent latent variables of null hypothesis global test.

matrix of the concatenate predictor latent variables of null hypothesis global test.

vector of the concatenate indipendent latent variables of alternative hypothesis global test.

matrix of the concatenate predictor latent variables of alternative hypothesis global test.

string indicating the method: LM or LAD

method

Further arguments passed on to <code><a rd-options="" href="/link/Fg.test.pls?package=genpathmox&version=0.6" data-mini-rdoc="genpathmox::Fg.test.pls">Fg.test.pls</a></code>.

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internal

It provides an interesting solution for handling a high number
of segmentation variables in partial least squares structural equation
modeling. The package implements the "Pathmox" algorithm (Lamberti, Sanchez,
and Aluja,(2016)<doi:10.1002/asmb.2168>) including the F-coefficient
test (Lamberti, Sanchez, and Aluja,(2017)<doi:10.1002/asmb.2270>)
to detect the path coefficients responsible for the identified differences),
the hybrid multi-group approach (Lamberti (2021)
<doi:10.1007/s11135-021-01096-9>) and the classical multi-group
approaches (parametric and permutation approaches). The package also
includes an extension of the "Pathmox" algorithm to the case of
linear regression models.

Giuseppe Lamberti

genpathmox

Generalized Pathmox Approach Segmentation Tree Analysis

Fg.test.pls function

Further arguments passed on to <code><a rd-options='' href='Fg.test.pls'>Fg.test.pls</a></code>.

Fg.test.pls: F-Global test.

Description

Usage

Arguments

Value

Details