findFactorTotalVar {simsem} | R Documentation |
Find factor total variances from regression coefficient matrix, factor (residual) correlations, and factor residual variances
Description
Find factor total variances from regression coefficient matrix, factor (residual) correlation matrix, and factor residual variances for latent variable models. In the path analysis model, this function will find indicator total variances from regression coefficient, indicator (residual) correlation matrix, and indicator residual variances.
Usage
findFactorTotalVar(beta, corPsi, residualVarPsi, gamma = NULL, covcov = NULL)
Arguments
beta |
Regression coefficient matrix among factors |
corPsi |
Factor or indicator residual correlations. |
residualVarPsi |
Factor or indicator residual variances. |
gamma |
Regression coefficient matrix from covariates (column) to factors (rows) |
covcov |
A covariance matrix among covariates |
Value
A vector of factor (indicator) total variances
Author(s)
Sunthud Pornprasertmanit (psunthud@gmail.com)
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 -
findFactorResidualVar
to find factor residual variances -
findFactorTotalCov
to 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
residualVar <- c(1, 1, 1, 0.64, 0.288, 0.288, 0.64, 0.29568, 0.21888)
findFactorTotalVar(path, facCor, residualVar)