Sigmathetafromsigma2: Model-Implied Variance-Covariance Matrix

Description Usage Arguments Details Author(s) See Also Examples

View source: R/ram.R

Description

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

Usage

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Sigmathetafromsigma2(taudot, beta, alpha, sigma2x, sigma2m, sigma2y)

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).

sigma2m

Numeric. Variance of m ≤ft( σ_{m}^{2} \right) .

sigma2y

Numeric. Variance of y ≤ft( σ_{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(), Sigmatheta(), S(), mutheta()

Examples

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Sigmathetafromsigma2(
  taudot = 0.207648,
  beta = 0.451039,
  alpha = 0.338593,
  sigma2x = 1.2934694,
  sigma2m = 1.0779592,
  sigma2y = 1.2881633
)
cov(jeksterslabRdatarepo::thirst)

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