scaleWeights

<p>The (K x K) empirical indicator correlation matrix.</p>

<p>Scale weights such that the formed composite has unit variance.</p>

internal

Estimate, assess, test, and study linear, nonlinear, hierarchical
and multigroup structural equation models using composite-based approaches
and procedures, including estimation techniques such as partial least squares
path modeling (PLS-PM) and its derivatives (PLSc, ordPLSc, robustPLSc),
generalized structured component analysis (GSCA), generalized structured
component analysis with uniqueness terms (GSCAm), generalized canonical
correlation analysis (GCCA), principal component analysis (PCA),
factor score regression (FSR) using sum score, regression or
bartlett scores (including bias correction using Croon<e2><80><99>s approach),
as well as several tests and typical postestimation procedures
(e.g., verify admissibility of the estimates, assess the model fit,
test the model fit etc.).

Manuel Rademaker

cSEM

Composite-Based Structural Equation Modeling

Manuel E. Rademaker

Florian Schuberth

Tamara Schamberger

Michael Klesel

Theo K. Dijkstra

J<c3><b6>rg Henseler

scaleWeights function

Internal: Scale weights — scaleWeights

Internal: Scale weights

scaleWeights: Internal: Scale weights

Description

Usage

Arguments

Value