simsem: findFactorTotalCov – R documentation

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findFactorTotalCov

Find factor total covariance from regression coefficient matrix, factor residual covariance

Description

Find factor total covariances from regression coefficient matrix, factor residual covariance matrix. The residual covaraince matrix might be derived from factor residual correlation, total variance, and error variance. This function can be applied for path analysis model as well.

Usage

findFactorTotalCov(beta, psi = NULL, corPsi = NULL, totalVarPsi = NULL, 
    errorVarPsi = NULL, gamma = NULL, covcov = NULL)

Arguments

`beta`	Regression coefficient matrix among factors
`psi`	Factor or indicator residual covariances. This argument can be skipped if factor residual correlation and either total variances or error variances are specified.
`corPsi`	Factor or indicator residual correlation. This argument must be specified with total variances or error variances.
`totalVarPsi`	Factor or indicator total variances.
`errorVarPsi`	Factor or indicator residual variances.
`gamma`	Regression coefficient matrix from covariates (column) to factors (rows)
`covcov`	A covariance matrix among covariates

Value

A matrix of factor (model-implied) total covariance

Author(s)

Sunthud Pornprasertmanit (psunthud@gmail.com)

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)
findFactorTotalCov(path, corPsi=facCor, errorVarPsi=residualVar)

simsem

SIMulated Structural Equation Modeling

v0.5-16

GPL (>= 2)

Authors

Sunthud Pornprasertmanit [aut], Patrick Miller [aut], Alexander Schoemann [aut] (<https://orcid.org/0000-0002-8479-8798>), Terrence D. Jorgensen [aut, cre] (<https://orcid.org/0000-0001-5111-6773>), Corbin Quick [ctb]

Initial release

2021-03-28