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localIV

0.3.1

Estimation of Marginal Treatment Effects using Local Instrumental Variables

0packages depend
2.6Kdownloads / year
test coverage
0/13checks pass

Overview

About
Maintained by Xiang ZhouFirst published 2018-08-055 releasesCRAN page ↗GitHub ↗

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.

Install

Health

CRAN checks
13NOTE
Failing flavors
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  • NOTE r-devel-windows-x86_64
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  • NOTE r-oldrel-windows-x86_64
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  • NOTE r-release-macos-x86_64
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Slowest check: 1.5 min · r-oldrel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
5
Dependencies · direct
Check history
  • NOTE2026-06-09
    0 OK · 13 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    0 OK · 12 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • NOTE2026-03-10
    0 OK · 14 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 378 wordsVignettesNopkgdown siteNoNEWSYes · 67% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
60%

Downloads

2.6K
CRAN downloads in the past year
Rank #15,923 · ~7/day · ~213/mo
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66890 days
2.6K1 year
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Repository

Repository
6Stars
2Forks
1Open issues
0Open PRs
0Releases
50Commits
1Contributors
50 commits · Last activity 2020-06-26

Stars over time

2025-03-30 · 62026-07-07 · 6

Repository practices

Upstream repositoryBeta

3 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/xiangzhou09/localiv on 2026-07-31.

Continuous integration (1)
Travis CI
Docs source (1)
README.Rmd
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
5 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.3.0
Imports (5)
KernSmoothmgcvrlangsampleSelectionstats
LinkingTo (0)
none
Suggests (3)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (1)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Package Timeline

5 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • 0.3.1Latest
    2020-06-26 · current release · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
  • 0.3.0
    2020-04-01 · diff ↗
  • 0.2.1
    2019-05-06 · diff ↗
  • 0.2.0
    2019-04-28 · diff ↗
  • R
    R 3.6.0 released · 2019-04-26
  • 0.1.0
    2018-08-05
  • R
    R 3.5.0 released · 2018-04-23

Package metadata

First published
2018-08-05
Total releases
5 / 8 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 3.3.0
Bundled data
230 KB / 1 file
Download size
269 KB
Installed size
not tracked yet
With dependencies
not tracked yet
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