check_blocks

<p>list defining the blocks of manifest variables. Elements in
<code>blocks</code> must have the same mode: all "numeric" or all "character".</p>

blocks

<p>matrix or data frame from where to extract manifest variables.</p>

Data

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.

Last chance! 50% off unlimited learning

check_blocks: Check well defined blocks

Description

Usage

Arguments

Value

Details