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eff2
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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]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-21
Latest Update: 2024-01-26
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 29 Jun. 2026.
Other packages that cited eff2 R package
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imports, suggests or enhances
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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