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leakyIV  

Leaky Instrumental Variables
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("leakyIV", "0.0.1")



Attach the package and use:
library("leakyIV")
Maintained by
David S. Watson
[Scholar Profile | Author Map]
First Published: 2024-04-09
Latest Update: 2024-04-09
Description:
Instrumental variables (IVs) are a popular and powerful tool for estimating causal effects in the presence of unobserved confounding. However, classical methods rely on strong assumptions such as the exclusion criterion, which states that instrumental effects must be entirely mediated by treatments. In the so-called "leaky" IV setting, candidate instruments are allowed to have some direct influence on outcomes, rendering the average treatment effect (ATE) unidentifiable. But with limits on the amount of information leakage, we may still recover sharp bounds on the ATE, providing partial identification. This package implements methods for ATE bounding in the leaky IV setting with linear structural equations. For details, see Watson et al. (2024) .
How to cite:
David S. Watson (2024). leakyIV: Leaky Instrumental Variables. R package version 0.0.1, https://cran.r-project.org/web/packages/leakyIV. Accessed 22 Feb. 2025.
Previous versions and publish date:
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