averageR2w

(n,p)-matrix, the values of the manifest variables.
The columns must be arranged in that way that the components of refl are (absolutely) increasing.

(q,q) lower triangular matrix describing the interrelations of the latent variables:
b_ij = 1 regression coefficient of eta_j in the regression relation in which eta_i is the depend variable 
b_ij = 0 if eta_i does not depend on eta_j in a direct way (b_ii = 0 !)

vector describing with which exogenous composite the X-variables are connected

indicatorx

vector describing with which endogenous composite the Y-variables are connected

indicatory

logical TRUE when there are loadings for the X-variables in the model

loadingx

logical TRUE when there are loadings for the Y-variables in the model

loadingy

vector of length n, indicating the cluster the observation belongs to

member

<code>averageR2w</code> computes the weighted average of average of coefficients of determination for the structural parts 
of a segmented GSC model

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.

averageR2w: For use in boottestgscm.

Description

Usage

Arguments

Value