Package: adace 1.0.2

adace: Estimator of the Adherer Average Causal Effect

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>.

Authors:Jiaxun Chen [aut], Rui Jin [aut], Yongming Qu [aut], Run Zhuang [aut, cre], Ying Zhang [aut], Eli Lilly and Company [cph]

adace_1.0.2.tar.gz
adace_1.0.2.zip(r-4.7)adace_1.0.2.zip(r-4.6)adace_1.0.2.zip(r-4.5)
adace_1.0.2.tgz(r-4.6-any)adace_1.0.2.tgz(r-4.5-any)
adace_1.0.2.tar.gz(r-4.7-any)adace_1.0.2.tar.gz(r-4.6-any)
adace_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
adace/json (API)
NEWS

# Install 'adace' in R:
install.packages('adace', repos = c('https://zhuangr.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 2 scripts 221 downloads 4 exports 12 dependencies

Last updated from:9607f71848. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE132
source / vignettesOK166
linux-release-x86_64NOTE128
macos-release-arm64NOTE121
macos-oldrel-arm64NOTE97
windows-develNOTE86
windows-releaseNOTE90
windows-oldrelNOTE80
wasm-releaseOK105

Exports:est_S_Plus_Plus_MethodAest_S_Plus_Plus_MethodBest_S_Star_Plus_MethodAest_S_Star_Plus_MethodB

Dependencies:cligluelifecyclemagrittrplyrpracmaRcppreshape2rlangstringistringrvctrs