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SIRE  

Finding Feedback Effects in SEM and Testing for Their Significance
View on CRAN: Click here


Download and install SIRE package within the R console
Install from CRAN:
install.packages("SIRE")

Install from Github:
library("remotes")
install_github("cran/SIRE")

Install by package version:
library("remotes")
install_version("SIRE", "1.1.0")



Attach the package and use:
library("SIRE")
Maintained by
Gianmarco Vacca
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-07-30
Latest Update: 2019-04-11
Description:
Provides two main functionalities. 1 - Given a system of simultaneous equation, it decomposesthe 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>.
How to cite:
Gianmarco Vacca (2018). SIRE: Finding Feedback Effects in SEM and Testing for Their Significance. R package version 1.1.0, https://cran.r-project.org/web/packages/SIRE. Accessed 09 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:24), 1.0.2 (2018-07-30 15:20)
Other packages that cited SIRE R package
View SIRE citation profile
Other R packages that SIRE depends, imports, suggests or enhances
Complete documentation for SIRE
Functions, R codes and Examples using the SIRE R package
Some associated functions: causal_decompose . dec_calc . feedback_ml . macroIT . rho_calc . 
Some associated R codes: causal_decompose.R . dec_calc.R . feedback_ml.R . macroIT.R . rho_calc.R .  Full SIRE package functions and examples
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