F.data

############################################################################################

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 package also allows running the hybrid multi-group approach (Lamberti (2021)
<doi:10.1007/s11135-021-01096-9>).

Giuseppe Lamberti

genpathmox

Pathmox Approach Segmentation Tree Analysis

F.data function

<dl><dt>x</dt>
<dd>matrix or dataframe containing the data.</dd>
<dt>inner</dt>
<dd>a square (lower triangular) boolean matrix representing the inner model.</dd>
<dt>.model</dt>
<dd>A description of the user-specified model.</dd>
<dt>.scheme</dt>
<dd>string indicating the type of inner weighting
scheme. Possible values are <code>"centroid"</code>, <code>"factorial"</code>, or <code>"path"</code>.</dd>
<dt>.consistent</dt>
<dd>Logical. Should composite/proxy correlations be disattenuated 
to yield consistent loadings and path estimates if at least one of the construct 
is modeled as a common factor. Defaults to TRUE.</dd>
<dt>modtwo</dt>
<dd>vector indicating the binary partition.</dd></dl>

Arguments

Data preprocessing for F-tests — F.data

<dl>

<dt>x</dt>
<dd>matrix or dataframe containing the data.</dd>


<dt>inner</dt>
<dd>a square (lower triangular) boolean matrix representing the inner model.</dd>


<dt>.model</dt>
<dd>A description of the user-specified model.</dd>


<dt>.scheme</dt>
<dd>string indicating the type of inner weighting
scheme. Possible values are <code>"centroid"</code>, <code>"factorial"</code>, or <code>"path"</code>.</dd>


<dt>.consistent</dt>
<dd>Logical. Should composite/proxy correlations be disattenuated 
to yield consistent loadings and path estimates if at least one of the construct 
is modeled as a common factor. Defaults to TRUE.</dd>


<dt>modtwo</dt>
<dd>vector indicating the binary partition.</dd>

</dl>

F.data: Data preprocessing for F-tests

Description

Usage

Value

Arguments

Details