S Matrix

Matrix of variance of x and error variances from the simple mediation model.

S(sigma2x, sigma2epsilonm, sigma2epsilony)

Arguments

sigma2x	Numeric. Variance of x \(\left( \sigma_{x}^{2} \right)\).
sigma2epsilonm	Numeric. Error variance of \(\varepsilon_{m_{i}}\) \(\left( \sigma_{\varepsilon_m}^{2} \right)\).
sigma2epsilony	Numeric. Error variance of \(\varepsilon_{y_{i}}\) \(\left( \sigma_{\varepsilon_y}^{2} \right)\).

Details

The simple mediation model is given by $$ y_i = \delta_y + \dot{\tau} x_i + \beta m_i + \varepsilon_{y_{i}} $$

$$ m_i = \delta_m + \alpha x_i + \varepsilon_{m_{i}} $$

The parameters for the mean structure are $$ \boldsymbol{\theta}_{\text{mean structure}} = \left\{ \mu_x, \delta_m, \delta_y \right\} . $$

The parameters for the covariance structure are $$ \boldsymbol{\theta}_{\text{covariance structure}} = \left\{ \dot{\tau}, \beta, \alpha, \sigma_{x}^{2}, \sigma_{\varepsilon_{m}}^{2}, \sigma_{\varepsilon_{y}}^{2} \right\} . $$

See also

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

Author

Ivan Jacob Agaloos Pesigan

Examples

S(
  sigma2x = 1.293469,
  sigma2epsilonm = 0.9296691,
  sigma2epsilony = 0.9310597
)
#>          x         m         y
#> x 1.293469 0.0000000 0.0000000
#> m 0.000000 0.9296691 0.0000000
#> y 0.000000 0.0000000 0.9310597