Sigmatheta: Model-Implied Variance-Covariance Matrix

In jeksterslabds/jeksterslabRmedsimple: Jekster's Lab Simple Mediation Model Utilities

Description

Model-implied variance-covariance matrix from the simple mediation model.

Usage

Sigmatheta(taudot, beta, alpha, sigma2x, sigma2epsilonm, sigma2epsilony)

Arguments

taudot	Numeric. Slope of path from x to y ≤ft( \dot{τ} \right).
beta	Numeric. Slope of path from m to y ≤ft( β \right) .
alpha	Numeric. Slope of path from x to m ≤ft( α \right) .
sigma2x	Numeric. Variance of x ≤ft( σ_{x}^{2} \right).
sigma2epsilonm	Numeric. Error variance of \varepsilon_{m_{i}} ≤ft( σ_{\varepsilon_m}^{2} \right).
sigma2epsilony	Numeric. Error variance of \varepsilon_{y_{i}} ≤ft( σ_{\varepsilon_y}^{2} \right).

Details

The simple mediation model is given by

y_i = δ_y + \dot{τ} x_i + β m_i + \varepsilon_{y_{i}}

m_i = δ_m + α x_i + \varepsilon_{m_{i}}

The parameters for the mean structure are

\boldsymbol{θ}_{\text{mean structure}} = ≤ft\{ μ_x, δ_m, δ_y \right\} .

The parameters for the covariance structure are

\boldsymbol{θ}_{\text{covariance structure}} = ≤ft\{ \dot{τ}, β, α, σ_{x}^{2}, σ_{\varepsilon_{m}}^{2}, σ_{\varepsilon_{y}}^{2} \right\} .

Author(s)

Ivan Jacob Agaloos Pesigan

See Also

Other reticular action model functions: A.std(), A(), Mfrommu(), M(), S.std(), Sfromsigma2(), Sigmatheta.std(), Sigmathetafromsigma2(), S(), mutheta()

Examples

Sigmatheta(
  taudot = 0.207648,
  beta = 0.451039,
  alpha = 0.338593,
  sigma2x = 1.293469,
  sigma2epsilonm = 0.9296691,
  sigma2epsilony = 0.9310597
)
cov(jeksterslabRdatarepo::thirst)

jeksterslabds/jeksterslabRmedsimple documentation built on Oct. 16, 2020, 11:30 a.m.