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localIV
View on CRAN: Click
here
Download and install localIV package within the R console
Install from CRAN:
install.packages("localIV")
Install from Github:
library("remotes")
install_github("cran/localIV") Install by package version:
library("remotes")
install_version("localIV", "0.3.2") Attach the package and use:
library("localIV")
Maintained by
Xiang Zhou
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-08-05
Latest Update: 2020-06-26
Description:
In the generalized Roy model, the marginal treatment effect (MTE) can be used as
a building block for constructing conventional causal parameters such as the average treatment
effect (ATE) and the average treatment effect on the treated (ATT). Given a treatment selection
equation and an outcome equation, the function mte() estimates the MTE via the semiparametric
local instrumental variables method or the normal selection model. The function mte_at() evaluates
MTE at different values of the latent resistance u with a given X = x, and the function mte_tilde_at()
evaluates MTE projected onto the estimated propensity score. The function ace() estimates
population-level average causal effects such as ATE, ATT, or the marginal policy relevant
treatment effect.
How to cite:
Xiang Zhou (2018). localIV: Estimation of Marginal Treatment Effects using Local Instrumental Variables. R package version 0.3.2, https://cran.r-project.org/web/packages/localIV. Accessed 27 Oct. 2026.
Previous versions and publish date:
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Complete documentation for localIV
Functions, R codes and Examples using
the localIV R package
Some associated functions: ace . mte . mte_at . mte_tilde_at . toydata .
Some associated R codes: ace.R . data.R . mte.R . mte_at.R . mte_localIV.R . mte_normal.R . mte_tilde_at.R . utils.R . Full localIV package functions and examples
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