semTools (version 0.3-0)

impliedFactorStat: Calculate the model-implied factor means and covariance matrix.

Description

Calculate reliability values of factors by coefficient omega

Usage

impliedFactorStat(object)
impliedFactorMean(object)
impliedFactorCov(object)

Arguments

object

The lavaan model object provided after running the cfa, sem, growth, or lavaan functions.

Value

• Model-implied factor means or model-implied factor covariance matrix, or both

Details

The impliedFactorMean function is used to calculated model-implied factor means: $$\mu = \left( \bold{I} - \bold{B} \right)^{-1} \alpha ,$$ where $\mu$ is the model-implied factor mean, $\bold{I}$ is an identity matrix, $\bold{B}$ is an regression coefficient matrix, and $\alpha$ is a vector of factor intercepts. The impliedFactorCov function is used to calculated model-implied covariance matrix: $$\Phi = \left( \bold{I} - \bold{B} \right)^{-1} \Psi \left(\bold{I} - \bold{B} \right)^{-1\prime} ,$$ where $\Phi$ is the model-implied factor covariance matrix, $\Psi$ is the residual factor covariance matrix. The impliedFactorStat function is used to provide both model-implied means (if the mean structure is estimated) and covariance matrix.

Examples

HS.model <- ' visual  =~ x1 + x2 + x3
              textual =~ x4 + x5 + x6
              speed   =~ x7 + x8 + x9 '

fit <- cfa(HS.model, data=HolzingerSwineford1939, group="school")
impliedFactorStat(fit)