SIRE: Finding Feedback Effects in SEM and Testing for Their
Significance
Provides two main functionalities.
1 - Given a system of simultaneous equation,
it decomposes the matrix of coefficients weighting the endogenous variables
into three submatrices: one includes the subset of coefficients that have a causal nature
in the model, two include the subset of coefficients that have a interdependent nature
in the model, either at systematic level or induced by the correlation between error terms.
2 - Given a decomposed model,
it tests for the significance of the interdependent relationships acting in the system,
via Maximum likelihood and Wald test, which can be built starting from the function output.
For theoretical reference see Faliva (1992) <doi:10.1007/BF02589085> and
Faliva and Zoia (1994) <doi:10.1007/BF02589041>.
| Version: |
1.1.0 |
| Depends: |
R (≥ 3.1.0) |
| Imports: |
systemfit, psych, igraph, matrixcalc, MASS, numDeriv, Matrix, stringr, Rsolnp, dplyr, magrittr |
| Published: |
2019-04-11 |
| DOI: |
10.32614/CRAN.package.SIRE |
| Author: |
Gianmarco Vacca [aut, cre] |
| Maintainer: |
Gianmarco Vacca <gianmarco.vacca at unicatt.it> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| CRAN checks: |
SIRE results |
Documentation:
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