Description Usage Arguments Details Value Author(s) References See Also
Derives the model-implied variance-covariance matrix \boldsymbol{Σ} ≤ft( \boldsymbol{θ} \right) using the Reticular Action Model (RAM) notation.
1 | ramSigmatheta(A, S, filter)
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A |
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S |
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filter |
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The model-implied variance-covariance matrix \boldsymbol{Σ} ≤ft( \boldsymbol{θ} \right) as a function of Reticular Action Model (RAM) matrices is given by
\boldsymbol{Σ} ≤ft( \boldsymbol{θ} \right) = \mathbf{F} ≤ft( \mathbf{I} - \mathbf{A} \right)^{-1} \mathbf{S} ≤ft[ ≤ft( \mathbf{I} - \mathbf{A} \right)^{-1} \right]^{T} \mathbf{F}^{T}
where
\mathbf{A}_{m \times m} represents asymmetric paths (single-headed arrows), such as regression coefficients and factor loadings,
\mathbf{S}_{m \times m} represents symmetric paths (double-headed arrows), such as variances and covariances,
\mathbf{F}_{k \times m} represents the filter matrix used to select the observed variables,
\mathbf{I}_{m \times m} represents an identity matrix,
k number of observed variables,
q number of latent variables, and
m number of observed and latent variables, that is k + q .
Returns the model-implied variance-covariance matrix
\boldsymbol{Σ} ≤ft( \boldsymbol{θ} \right)
derived from the A
, S
, and filter
matrices.
Ivan Jacob Agaloos Pesigan
McArdle, J. J. (2013). The development of the RAM rules for latent variable structural equation modeling. In A. Maydeu-Olivares & J. J. McArdle (Eds.), Contemporary Psychometrics: A festschrift for Roderick P. McDonald (pp. 225–273). Lawrence Erlbaum Associates.
McArdle, J. J., & McDonald, R. P. (1984). Some algebraic properties of the Reticular Action Model for moment structures. British Journal of Mathematical and Statistical Psychology, 37 (2), 234–251.
Other SEM notation functions:
ramM()
,
rammutheta()
,
ramsigma2()
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