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
NeedsCompilation: no
Packaged: 2020-06-26 15:17:35 UTC; Xiang
Author: Xiang Zhou [aut, cre]
Maintainer: Xiang Zhou <xiang_zhou@fas.harvard.edu>
Repository: CRAN
Date/Publication: 2020-06-26 15:40:02 UTC
Built: R 4.6.0; ; 2026-04-25 14:08:45 UTC; unix
