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npsr  

Validate Instrumental Variables using NPS
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("npsr", "0.1.1")



Attach the package and use:
library("npsr")
Maintained by
Fabian Sellmann
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-05-18
Latest Update:
Description:
An R implementation of the Necessary and Probably Sufficient (NPS) test for finding valid instrumental variables, as suggested by Amit Sharma (2016, Working Paper) . The NPS test, compares the likelihood that a given set of observational data of the three variables Z, X and Y is generated by a valid instrumental variable model (Z -> X -> Y) to the likelihood that the data is generated by an invalid IV model.
How to cite:
Fabian Sellmann (2018). npsr: Validate Instrumental Variables using NPS. R package version 0.1.1, https://cran.r-project.org/web/packages/npsr. Accessed 25 Jun. 2026.
Previous versions and publish date:
0.1.1 (2018-05-18 16:33)
Other packages that cited npsr R package
View npsr citation profile
Other R packages that npsr depends, imports, suggests or enhances
Functions, R codes and Examples using the npsr R package
Some associated functions: Create_P . M_air . M_air_excl . M_excl . XY_product . Z_product . estimate_integral . make_proposer . make_sampler . nps.invalid . nps.necessary . nps.test . nps.valid . product_fraction . starting_points . 
Some associated R codes: RNested.R . npsCommon.R . npsInvalid.R . npsMain.R . npsNecessary.R . npsValid.R .  Full npsr package functions and examples
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