calculateOuterWeightsPLS

A <code>data.frame</code> or a <code>matrix</code> of standardized or unstandardized
data (indicators/items/manifest variables). Possible column types or classes
of the data provided are: "<code>logical</code>", "<code>numeric</code>" ("<code>double</code>" or "<code>integer</code>"),
"<code>factor</code>" ("<code>ordered</code>" and/or "<code>unordered</code>"), "<code>character</code>" (converted to factor),
or a mix of several types.

.data

The (K x K) empirical indicator correlation matrix.

A (J x J) matrix of inner weights.

A vector giving the mode for each construct in the form <code>"name" = "mode"</code>.
Only used internally.

.modes

Calculates outer weights in PLS-PM. Currently, the originally suggested mode A
and mode B are suggested. Additionally, non-negative least squares (modeBNNLS) and
weights of principal component analysis (PCA) are implemented.

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

calculateOuterWeightsPLS: Internal: Calculate the outer weights for PLS-PM

Description

Usage

Arguments

Value