Standardized Model-Implied Variance-Covariance Matrix

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

Sigmatheta.std(
  taudotprime,
  betaprime,
  alphaprime,
  lambdax,
  lambdam,
  lambday,
  sigma2epsilonm,
  sigma2epsilony
)

Arguments

taudotprime	Numeric. Standardized slope of path from x to y \(\left( \dot{\tau}^{\prime} \right)\).
betaprime	Numeric. Standardized slope of path from m to y \(\left( \beta^{\prime} \right)\) .
alphaprime	Numeric. Standardized slope of path from x to m \(\left( \alpha^{\prime} \right)\) .
lambdax	Numeric. Factor loading xlatent ~ x \( \left( \lambda_x \right)\) . Numerically equivalent to the standard deviation of x.
lambdam	Numeric. Factor loading mlatent ~ m \( \left( \lambda_m \right)\) . Numerically equivalent to the standard deviation of m.
lambday	Numeric. Factor loading ylatent ~ y \( \left( \lambda_y \right)\) . Numerically equivalent to the standard deviation of y.
sigma2epsilonm	Numeric. Error variance of \(\varepsilon_{m_{latent_{i}}}\) \(\left( \sigma_{\varepsilon_{m_{latent}}}^{2} \right)\).
sigma2epsilony	Numeric. Error variance of \(\varepsilon_{y_{latent_{i}}}\) \(\left( \sigma_{\varepsilon_{y_{latent}}}^{2} \right)\).

See also

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

Author

Ivan Jacob Agaloos Pesigan

Examples

Sigmatheta.std(
  taudotprime = 0.2080748,
  betaprime = 0.4126006,
  alphaprime = 0.3708979,
  lambdax = 1.137308,
  lambdam = 1.038248,
  lambday = 1.134973,
  sigma2epsilonm = 0.8624347,
  sigma2epsilony = 0.7227811
)
#>           x         m         y
#> x 1.2934695 0.4379591 0.4661226
#> m 0.4379591 1.0779589 0.5771429
#> y 0.4661226 0.5771429 1.2881637
cov(jeksterslabRdatarepo::thirst)
#>             temp    thirst     water
#> temp   1.2934694 0.4379592 0.4661224
#> thirst 0.4379592 1.0779592 0.5771429
#> water  0.4661224 0.5771429 1.2881633