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 [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.html , abima.pdf

Downloads:

Package source:	abima_1.1.tar.gz
Windows binaries:	r-devel: abima_1.1.zip, r-release: abima_1.1.zip, 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

Linking:

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