Package: abima 1.0

abima: Adaptive Bootstrap Inference for Mediation Analysis with Enhanced Statistical Power

Assess whether and how a specific continuous or categorical exposure affects the outcome of interest through one- or multi-dimensional mediators using an adaptive bootstrap (AB) approach. The AB method allows to make inference for composite null hypotheses of no mediation effect, providing valid type I error control and thus optimizes statistical power. For more technical details, refer to He, Song and Xu (2024) <doi:10.1093/jrsssb/qkad129>.

Authors:Canyi Chen [aut, cre], Yinqiu He [aut], Gongjun Xu [aut], Peter X.-K. Song [aut, cph]

abima_1.0.tar.gz
abima_1.0.zip(r-4.5)abima_1.0.zip(r-4.4)abima_1.0.zip(r-4.3)
abima_1.0.tgz(r-4.4-any)abima_1.0.tgz(r-4.3-any)
abima_1.0.tar.gz(r-4.5-noble)abima_1.0.tar.gz(r-4.4-noble)
abima_1.0.tgz(r-4.4-emscripten)abima_1.0.tgz(r-4.3-emscripten)
abima.pdf |abima.html
abima/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/canyi-chen/abima/issues

On CRAN:

enhanced-powermediation-analysistype-i-error-control

3.30 score 7 scripts 3 exports 1 dependencies

Last updated 5 days agofrom:afc72cea01. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-winOKOct 26 2024
R-4.5-linuxOKOct 26 2024
R-4.4-winOKOct 26 2024
R-4.4-macOKOct 26 2024
R-4.3-winOKOct 26 2024
R-4.3-macOKOct 26 2024

Exports:abYlm.MglmabYlm.Mlmgenerate_all_data

Dependencies:boot