getF.Sigma: getF.Sigma

View source: R/effectSizes.R

getF.SigmaR Documentation

getF.Sigma

Description

Computes the minimum of the chosen fitting-function given the model-implied and the observed (or population) covariance matrix. The ML fitting function is: F_min = tr(S %*% SigmaHat^-1) - p + ln(det(SigmaHat)) - ln(det(S)). When a meanstructure is included, ⁠(mu - muHat)' SigmaHat^-1 (mu - muHat)⁠ is added. The WLS fitting function is: ⁠F_min = (Sij - SijHat)' V (Sij - SijHat)⁠ where V is the inverse of N times the asymptotic covariance matrix of the sample statistics (Gamma; N x ACOV(mu, vech(S))). For DWLS, V is the diagonal of the inverse of diag(NACOV), i.e. diag(solve(diag(Gamma))). For ULS, V = I. ULS has an unknown asymptotic distribution, so it is actually irrelevant, but provided for the sake of completeness.

Usage

getF.Sigma(SigmaHat, S, muHat = NULL, mu = NULL, fittingFunction = "ML")

Arguments

SigmaHat

model implied covariance matrix

S

observed (or population) covariance matrix

muHat

model implied mean vector

mu

observed (or population) mean vector

fittingFunction

one of ML (default), WLS, DWLS, ULS

Value

Returns Fmin


semPower documentation built on Nov. 15, 2023, 1:08 a.m.