invariance

matrix or data.frame with the data.

A square (lower triangular) boolean matrix representing the inner 
model (i.e. the path relationships between latent variables).

inner

list of vectors with column indices or column names from Data indicating 
the sets of manifest variables forming each block (i.e. which manifest variables correspond to each block).

outer

character vector indicating the type of measurement for each
block. Possible values are: <code>"A", "B", "newA", "PLScore", "PLScow"</code>. 
The length of <code>mode</code> must be equal to the length of <code>outer</code>.

mode

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

scheme

optional list of string vectors indicating the type of 
measurement scale for each manifest variable specified in <code>blocks</code>.
<code>scaling</code> must be specified when working with non-metric variables.
Possible values: <code>"num"</code> (numeric), <code>"raw"</code>, <code>"nom"</code> (nominal), 
and <code>"ord"</code> (ordinal).

scaling

whether manifest variables should be standardized. 
Only used when <code>scaling = NULL</code>. When (<code>TRUE</code>, data is 
scaled to standardized values (mean=0 and variance=1).

scaled

internal

Provides a very interesting solution for
handling segmentation variables in complex statistical methodology. It
contains en extended version of the "Pathmox" algorithm (Lamberti, Sanchez
and Aluja,(2016)<doi:10.1002/asmb.2168>) in the context of
Partial Least Squares Path Modeling including the F-block
test (to detect the responsible latent endogenous equations of the
difference), the F-coefficient (to detect the path coefficients responsible
of the difference) and the "invariance" test (to realize a comparison
between the sub-models' latent variables). Furthermore, the package
contains a generalized version of the "Pathmox" algorithm to approach
different methodologies: linear regression and least absolute regression
models.

invariance: Calculating the invariance test

Description

Usage

Arguments

Value

Details