Package: localIV
Type: Package
Title: Estimation of Marginal Treatment Effects using Local
        Instrumental Variables
Version: 0.2.0
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) (Heckman, Urzua, and Vytlacil 2006
  <doi:10.1162/rest.88.3.389>). Given a treatment selection model and an outcome model, the function mte()
  estimates the MTE via a semiparametric local instrumental variables method (or via a normal selection model).
  The function eval_mte() evaluates MTE at any combination of covariates x and latent resistance u, and the
  function eval_mte_tilde() evaluates MTE projected onto the estimated propensity score (Zhou and Xie 2019
  <https://www.journals.uchicago.edu/doi/abs/10.1086/702172>). The object returned by mte() can be used to
  estimate conventional parameters such as ATE, ATT, and ATU (via average()) or marginal policy-relevant
  treatment effects (via mprte()).
Depends: R (>= 3.3.0)
Imports: KernSmooth (>= 2.5.0), mgcv (>= 1.8-19), sampleSelection (>=
        1.2-0), stats
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
URL: https://github.com/xiangzhou09/localIV
BugReports: https://github.com/xiangzhou09/localIV
NeedsCompilation: no
Packaged: 2019-04-28 15:04:34 UTC; Xiang
Author: Xiang Zhou [aut, cre]
Maintainer: Xiang Zhou <xiang_zhou@fas.harvard.edu>
Repository: CRAN
Date/Publication: 2019-04-28 19:20:08 UTC
