gscmcovout

A list containing the result of gscmcov for the simplemodel data.

datasets

The composites are linear combinations of their indicators in composite based structural equation models. Structural models are considered consisting of two blocks. The indicators of the exogenous composites are named by X, the indicators of the endogenous by Y. Reflective relations are given by arrows pointing  from the composite to their indicators. Their values are called loadings.  In a reflective-reflective scenario all indicators have loadings. Arrows are pointing to their indicators only from the endogenous composites in  the formative-reflective scenario. There are no loadings at all in the formative-formative scenario. The covariance matrices are computed for these three scenarios. They can be used to simulate these models. These models can also be estimated and a segmentation procedure is included as well.

Rainer Schlittgen

cbsem

Simulation, Estimation and Segmentation of Composite Based
Structural Equation Models

gscmcovout function

A list with entries:<dl class="dl-horizontal">
 <dt>$S</dt><dd>Covariance matrix of manifest variables</dd> 
 <dt>$B</dt><dd>Design matrix of the simple model</dd>
 <dt>$Scomp</dt><dd>Covariance matrix of composites</dd>
 <dt>$wx</dt><dd>weighting vector for exogenous composites</dd>
 <dt>$wy</dt><dd>weighting vector for endogenous composites</dd>
 <dt>$Sdd</dt><dd>diagonal covariance matrix of errors for loadings of X-variables</dd>
 <dt>$See</dt><dd>diagonal covariance matrix of errors for loadings of Y-variables</dd>
</dl>

Format

Output of covgscmodel for the simplemodel data. — gscmcovout

A list with entries:<dl class='dl-horizontal'>
 <dt>$S</dt><dd>Covariance matrix of manifest variables</dd> 
 <dt>$B</dt><dd>Design matrix of the simple model</dd>
 <dt>$Scomp</dt><dd>Covariance matrix of composites</dd>
 <dt>$wx</dt><dd>weighting vector for exogenous composites</dd>
 <dt>$wy</dt><dd>weighting vector for endogenous composites</dd>
 <dt>$Sdd</dt><dd>diagonal covariance matrix of errors for loadings of X-variables</dd>
 <dt>$See</dt><dd>diagonal covariance matrix of errors for loadings of Y-variables</dd>
</dl>

gscmcovout: Output of covgscmodel for the simplemodel data.

Description

Usage

Arguments

Format