| findFactorResidualVar {simsem} | R Documentation | 
Find factor residual variances from regression coefficient matrix, factor (residual) correlations, and total factor variances
Description
Find factor residual variances from regression coefficient matrix, factor (residual) correlation matrix, and total factor variances for latent variable models. In the path analysis model, this function will find indicator residual variances from regression coefficient, indicator (residual) correlation matrix, and total indicator variances.
Usage
findFactorResidualVar(beta, corPsi, totalVarPsi = NULL, gamma = NULL, covcov = NULL)
Arguments
beta | 
 Regression coefficient matrix among factors  | 
corPsi | 
 Factor or indicator residual correlations.  | 
totalVarPsi | 
 Factor or indicator total variances. The default is that all factor or indicator total variances are 1.  | 
gamma | 
 Regression coefficient matrix from covariates (column) to factors (rows)  | 
covcov | 
 A covariance matrix among covariates  | 
Value
A vector of factor (indicator) residual variances
Author(s)
Sunthud Pornprasertmanit (psunthud@gmail.com)
See Also
-  
findIndInterceptto find indicator (measurement) intercepts -  
findIndMeanto find indicator (measurement) total means -  
findIndResidualVarto find indicator (measurement) residual variances -  
findIndTotalVarto find indicator (measurement) total variances -  
findFactorInterceptto find factor intercepts -  
findFactorMeanto find factor means -  
findFactorTotalVarto find factor total variances -  
findFactorTotalCovto find factor covariances 
Examples
path <- matrix(0, 9, 9)
path[4, 1] <- path[7, 4] <- 0.6
path[5, 2] <- path[8, 5] <- 0.6
path[6, 3] <- path[9, 6] <- 0.6
path[5, 1] <- path[8, 4] <- 0.4
path[6, 2] <- path[9, 5] <- 0.4
facCor <- diag(9)
facCor[1, 2] <- facCor[2, 1] <- 0.4
facCor[1, 3] <- facCor[3, 1] <- 0.4
facCor[2, 3] <- facCor[3, 2] <- 0.4
totalVar <- rep(1, 9)
findFactorResidualVar(path, facCor, totalVar)