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eff2  

Efficient Least Squares for Total Causal Effects
View on CRAN: Click here


Download and install eff2 package within the R console
Install from CRAN:
install.packages("eff2")

Install from Github:
library("remotes")
install_github("cran/eff2")

Install by package version:
library("remotes")
install_version("eff2", "1.0.2")



Attach the package and use:
library("eff2")
Maintained by
Richard Guo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-21
Latest Update: 2021-09-30
Description:
Estimate a total causal effect from observational data under linearity and causal sufficiency. The observational data is supposed to be generated from a linear structural equation model (SEM) with independent and additive noise. The underlying causal DAG associated the SEM is required to be known up to a maximally oriented partially directed graph (MPDAG), which is a general class of graphs consisting of both directed and undirected edges, including CPDAGs (i.e., essential graphs) and DAGs. Such graphs are usually obtained with structure learning algorithms with added background knowledge. The program is able to estimate every identified effect, including single and multiple treatment variables. Moreover, the resulting estimate has the minimal asymptotic covariance (and hence shortest confidence intervals) among all estimators that are based on the sample covariance.
How to cite:
Richard Guo (2021). eff2: Efficient Least Squares for Total Causal Effects. R package version 1.0.2, https://cran.r-project.org/web/packages/eff2. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0.0 (2021-05-21 10:10), 1.0.1 (2021-09-30 22:40)
Other packages that cited eff2 R package
View eff2 citation profile
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Complete documentation for eff2
Functions, R codes and Examples using the eff2 R package
Some associated functions: eff2 . estimateEffect . ex1 . isIdentified . 
Some associated R codes: amenable.R . bucket.R . data.R . eff2.R . misc.R . utils.R .  Full eff2 package functions and examples
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