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noncompliance (version 0.2.2)

Causal Inference in the Presence of Treatment Noncompliance Under the Binary Instrumental Variable Model

Description

A finite-population significance test of the 'sharp' causal null hypothesis that treatment exposure X has no effect on final outcome Y, within the principal stratum of Compliers. A generalized likelihood ratio test statistic is used, and the resulting p-value is exact. Currently, it is assumed that there are only Compliers and Never Takers in the population.

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Install

install.packages('noncompliance')

Monthly Downloads

252

Version

0.2.2

License

GPL (>= 3)

Maintainer

Wen Wei Loh

Last Published

February 15th, 2016

Functions in noncompliance (0.2.2)

Check_ACDE_bounds

Bounds for the Average Controlled Direct Effect (ACDE).
Get_pvalues_CONT

Exact finite population p-values under the sharp null for Compliers.
FindMLE_CONT_H1_hypergeoR

Maximum Likelihood Estimate without assuming the sharp null for Compliers.
expand.grid.DT

Expand.grid using the data.table package.
ACE_bounds_posterior

Posterior bounds for the Average Causal Effect (ACE).
ACE_bounds_triangle.plot

"Triangle" plot of the posterior bounds for the Average Causal Effect (ACE).
ACE_bounds

Bounds for the Average Causal Effect (ACE).
Check_IV_ineqs

Check of the Instrumental Variable (IV) inequalities.
AllColTotalsH0_CONT

Finds all column totals for Compliers and Never Takers under the sharp null for Compliers.
AllPossiblyObsH0_CONT

Finite population sample space given an observed dataset.
FindMLE_CONT_H0_hypergeoR

Maximum Likelihood Estimate under the sharp null for Compliers.