Description Usage Arguments Details Value Author(s) References See Also
Model-implied variance-covariance matrix for \mathbf{y} variables (\boldsymbol{Σ}_{\mathbf{yy}} ≤ft( \boldsymbol{θ} \right)) using the LISREL notation for structural equations with latent variables.
1 | lisrel_yy(LY, TE, inv, GA, PS, PH)
|
LY |
\boldsymbol{Λ}_{\mathbf{y}} p \times m matrix of factor loadings (\boldsymbol{λ}). p is the number of observed indicators (\mathbf{y}) and m is the number of latent endogenous variables (\boldsymbol{η}). |
TE |
\boldsymbol{Θ_{\boldsymbol{ε}}} p \times p matrix of residual variances and covariances for \mathbf{y} (\boldsymbol{ε}). |
inv |
The inverse of |
GA |
\boldsymbol{Γ}_{m \times n} coefficient matrix for exogenous variables. |
PS |
\boldsymbol{Ψ}_{m \times m} variance-covariance of \boldsymbol{ζ}. \boldsymbol{ζ} is a matrix of residual variances and covariances in regression equations. |
PH |
\boldsymbol{Φ}_{n \times n} variance-covariance matrix of \boldsymbol{ξ}. |
\boldsymbol{Σ}_{\mathbf{yy}} ≤ft( \boldsymbol{θ} \right) = \boldsymbol{Λ}_{\mathbf{y}} ≤ft( \mathbf{I} - \mathbf{B} \right)^{-1} ≤ft( \boldsymbol{Γ} \boldsymbol{Φ} \boldsymbol{Γ}^{T} + \boldsymbol{Ψ} \right) ≤ft[ ≤ft( \mathbf{I} - \mathbf{B} \right)^{-1} \right]^{T} \boldsymbol{Λ}_{\mathbf{y}}^{T} + \boldsymbol{Θ}_{\boldsymbol{ε}}
Returns the model-implied variance-covariance matrix for
\mathbf{y}
(\boldsymbol{Σ}_{\mathbf{yy}} ≤ft( \boldsymbol{θ} \right))
derived from the
\boldsymbol{Λ}_{\mathbf{y}}
(LY),
\boldsymbol{Θ}_{\boldsymbol{ε}}
(TE),
\mathbf{B}
(BE),
\mathbf{I}
(I),
\boldsymbol{Γ}
(GA),
\boldsymbol{Ψ}
(PS),
and
\boldsymbol{Φ}
(PH)
matrices.
Ivan Jacob Agaloos Pesigan
Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.
Jöreskog, K. G., & Sörbom, D. (1996). Lisrel 8: User's reference guide (2nd ed.). Scientific Software.
Other SEM notation functions:
eqs_mu(),
eqs(),
lisrel_fa(),
lisrel_obs_xy(),
lisrel_obs_yx(),
lisrel_obs_yy(),
lisrel_obs(),
lisrel_xx(),
lisrel_xy(),
lisrel_yx(),
lisrel(),
ram_mu(),
ram_m(),
ram_s(),
ram(),
sem_fa(),
sem_lat(),
sem_obs()
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