gscmcov: Determination of the covariance matrix of a GSC model...

In cbsem: Simulation, Estimation and Segmentation of Composite Based Structural Equation Models

Description

gscmcov determines the covariance matrix of a GSC model. This is a wrapper for the functions gscmcovrr, gscmcovfr and gscmcovff

Usage

gscmcov(B, indicatorx, indicatory, lambdax = NULL, lambday = NULL,
  wx = NULL, wy = NULL, Sxixi, R2 = NULL)

Arguments

B	(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 !)
indicatorx	vector describing with which exogenous composite the X-variables are connected
indicatory	vector describing with which endogenous composite the Y-variables are connected
lambdax	vector of loadings of indicators for exogenous composites or NULL when there are no loadings for the X-variables in the model
lambday	vector of loadings of indicators for endogenous composites or NULL when there are no loadings for the Y-variables in the model
wx	vector of weights for building exogenous composites or NULL when loadings are present
wy	vector of weights for building endogenous composites or NULL when loadings are present
Sxixi	covariance matrix of exogenous composites
R2	vector of coefficients of determination for regressions belonging to the structural model

Value

out list with components

S	covariance matrix of manifest variables
B	(q,q) lower triangular matrix with possibly modified coefficients of the structural model
Scomp	covariance matrix of composites
wx	vector of weights for building exogenous composites
wy	vector of weights for building endoogenous composites
Sdd	diagonal matrix of variances of errors of X variable loadings or NA
See	diagonal matrix of variances of errors of Y variable loadings or NA

Examples

Sxixi <- matrix(c(1.0,  0.01,  0.01, 1),2,2)   
B <- matrix(c( 0,0,0, 0,0,0, 0.7,0.4,0),3,3,byrow=TRUE) 
indicatorx <- c(1,1,1,2,2,2)
indicatory <- c(1,1,1)                     
lambdax <- c(0.83,0.87,0.87,0.91,0.88,0.82)
lambday <- c(0.89,0.90,0.80)  
wx <- c(0.46, 0.31, 0.32, 0.34, 0.40, 0.37)
wy <- c(0.41, 0.39, 0.37)    
out <- gscmcov(B,indicatorx,indicatory,lambdax,lambday,wx=NULL,wy=NULL,Sxixi,R2=NULL)        

cbsem documentation built on May 2, 2019, 5:56 a.m.