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>.

Version: 1.1
Imports: boot, stats
Suggests: testthat (≥ 3.0.0)
Published: 2024-10-25
DOI: 10.32614/CRAN.package.abima
Author: Canyi Chen ORCID iD [aut, cre], Yinqiu He [aut], Gongjun Xu [aut], Peter X.-K. Song [aut, cph]
Maintainer: Canyi Chen <cychen.stats at outlook.com>
BugReports: https://github.com/canyi-chen/abima/issues
License: MIT + file LICENSE
URL: https://websites.umich.edu/~songlab/software.html#ABIMA, https://github.com/canyi-chen/abima
NeedsCompilation: no
Materials: README NEWS
CRAN checks: abima results

Documentation:

Reference manual: abima.pdf

Downloads:

Package source: abima_1.1.tar.gz
Windows binaries: r-devel: abima_1.1.zip, r-release: not available, r-oldrel: abima_1.1.zip
macOS binaries: r-release (arm64): abima_1.1.tgz, r-oldrel (arm64): abima_1.1.tgz, r-release (x86_64): abima_1.1.tgz, r-oldrel (x86_64): abima_1.1.tgz
Old sources: abima archive

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