simsem (version 0.5-16)

findFactorResidualVar: 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

See Also

• findIndIntercept to find indicator (measurement) intercepts

• findIndMean to find indicator (measurement) total means

• findIndResidualVar to find indicator (measurement) residual variances

• findIndTotalVar to find indicator (measurement) total variances

• findFactorIntercept to find factor intercepts

• findFactorMean to find factor means

• findFactorTotalVar to find factor total variances

• findFactorTotalCov to find factor covariances

Examples

# NOT RUN {
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)
# }