Package: localIV
Type: Package
Title: Estimation of Marginal Treatment Effects using Local
        Instrumental Variables
Version: 0.3.1
Authors@R: person("Xiang", "Zhou", email = "xiang_zhou@fas.harvard.edu",
  role = c("aut", "cre"))
Description: 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.
Depends: R (>= 3.3.0)
Imports: KernSmooth (>= 2.5.0), mgcv (>= 1.8-19), rlang (>= 0.4.4),
        sampleSelection (>= 1.2-0), stats
Suggests: dplyr, ggplot2, tidyr
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
URL: https://github.com/xiangzhou09/localIV
BugReports: https://github.com/xiangzhou09/localIV
Config/pak/sysreqs: cmake make libicu-dev
Repository: https://xiangzhou09.r-universe.dev
Date/Publication: 2020-06-26 15:22:17 UTC
RemoteUrl: https://github.com/xiangzhou09/localiv
RemoteRef: HEAD
RemoteSha: 23d308ab0b5feb2f9aefea83a685f05d8e3d5b63
NeedsCompilation: no
Packaged: 2026-06-20 06:17:36 UTC; root
Author: Xiang Zhou [aut, cre]
Maintainer: Xiang Zhou <xiang_zhou@fas.harvard.edu>