args_assess_dotdotdot

An integer or a numeric vector of significance levels.
Defaults to <code>0.05</code>.

.alpha

Logical. Should a closed-form confidence interval be computed?
Defaults to <code>FALSE</code>.

.closed_form_ci

Logical. Should the RMS_theta be computed using the
model-implied construct correlation matrix (<code>TRUE</code>) or the construct correlation matrix
based on V(eta) = WSW' divided by the square root of the respective
reliabilities (<code>FALSE</code>). Defaults to <code>FALSE</code>.

.model_implied

Logical. Should the degrees of freedom for the null model
be computed? Defaults to <code>FALSE</code>.

.null_model

Logical. Should a saturated structural model be used?
Defaults to <code>FALSE</code>.

.saturated

Character string. Which model-implied correlation
matrix is calculated?
One of "indicator" or "construct". Defaults to "indicator".

.type_vcv

A complete alphabetical list of all possible arguments accepted by <code>assess()</code>'s <code>...</code>
(dotdotdot) argument.

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.).

args_assess_dotdotdot: Internal: Complete list of assess()'s ... arguments

Description

Arguments

Details