DESCRIPTION

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