Package: localIV 0.3.1

localIV: Estimation of Marginal Treatment Effects using Local Instrumental Variables

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.

Authors:Xiang Zhou [aut, cre]

localIV_0.3.1.tar.gz
localIV_0.3.1.zip(r-4.7)localIV_0.3.1.zip(r-4.6)localIV_0.3.1.zip(r-4.5)
localIV_0.3.1.tgz(r-4.6-any)localIV_0.3.1.tgz(r-4.5-any)
localIV_0.3.1.tar.gz(r-4.7-any)localIV_0.3.1.tar.gz(r-4.6-any)
localIV_0.3.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
localIV/json (API)
NEWS

# Install 'localIV' in R:
install.packages('localIV', repos = c('https://xiangzhou09.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/xiangzhou09/localiv/issues

Datasets:
  • toydata - A Hypothetical Dataset for Illustrative Purpose

On CRAN:

Conda:

3.48 score 6 stars 10 scripts 208 downloads 6 exports 78 dependencies

Last updated from:23d308ab0b. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE137
source / vignettesOK175
linux-release-x86_64NOTE144
macos-release-arm64NOTE84
macos-oldrel-arm64NOTE84
windows-develNOTE84
windows-releaseNOTE100
windows-oldrelNOTE80
wasm-releaseOK130

Exports:acemtemte_atmte_localIVmte_normalmte_tilde_at

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdigestdoBydplyrfarverforecastFormulafracdiffgenericsggplot2gluegtableisobandKernSmoothlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmaxLikmgcvmicrobenchmarkminqamiscToolsmodelrmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7sampleSelectionsandwichscalesSparseMstringistringrsurvivalsystemfittibbletidyrtidyselecttimeDateurcautf8vctrsVGAMviridisLitewithrzoo