Package: adace
Title: Estimator of the Adherer Average Causal Effect
Version: 1.0.2
Authors@R: c(
  person(
    given = "Jiaxun",
    family = "Chen",
    role = "aut"
        ),
  person(
    given = "Rui",
    family = "Jin",
    role = "aut"
       ),
  person(
    given = "Yongming",
    family = "Qu",
    role = "aut"
        ),
  person(
    given = "Run",
    family = "Zhuang",
    role = c("aut", "cre"),
    email = "capecod0321@gmail.com"
        ),
  person(
    given = "Ying",
    family = "Zhang",
    role = "aut"
        ),
  person(
    family = "Eli Lilly and Company",
    role = "cph"
        )) 
Imports: reshape2, pracma
Description: Estimate the causal treatment effect for subjects that can adhere 
    to one or both of the treatments. Given longitudinal data with missing 
    observations, consistent causal effects are calculated. Unobserved potential
    outcomes are estimated through direct integration as described in: 
    Qu et al., (2019) <doi:10.1080/19466315.2019.1700157> and 
    Zhang et. al., (2021) <doi:10.1080/19466315.2021.1891965>. 
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.2.3
Depends: R (>= 4.0.0)
Suggests: testthat (>= 3.0.0), cubature (>= 2.0.4), MASS (>= 7.3-55)
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2023-08-27 21:10:05 UTC; capec
Author: Jiaxun Chen [aut],
  Rui Jin [aut],
  Yongming Qu [aut],
  Run Zhuang [aut, cre],
  Ying Zhang [aut],
  Eli Lilly and Company [cph]
Maintainer: Run Zhuang <capecod0321@gmail.com>
Repository: CRAN
Date/Publication: 2023-08-28 13:10:02 UTC
Built: R 4.4.0; ; 2024-04-30 03:06:29 UTC; unix
