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-any)adace_1.0.2.zip(r-4.6-any)adace_1.0.2.zip(r-4.5-any)
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✨
DESCRIPTION |NEWS
card.svg |card.png
adace/json (API)

# 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 344 downloads 4 exports 12 dependencies

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

TargetResultTimeFilesSyslog
linux-develNOTE107
source / vignettesOK209
linux-releaseNOTE116
macos-releaseNOTE157
macos-oldrelNOTE162
windows-develNOTE78
windows-releaseNOTE64
windows-oldrelNOTE87
wasm-releaseOK104

Exports:est_S_Plus_Plus_MethodAest_S_Plus_Plus_MethodBest_S_Star_Plus_MethodAest_S_Star_Plus_MethodB

Dependencies:cligluelifecyclemagrittrplyrpracmaRcppreshape2rlangstringistringrvctrs