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accmv: Inference with Available Complete-Case Missing Values

Implements inverse probability weighted, regression adjustment, and multiply robust estimators under the available complete-case missing value assumption of Cheng, Chen, Smith, and Zhao (2022) <doi:10.48550/arXiv.2207.02289>. Supports one or two primary variables, exponential-tilt sensitivity analysis, regression weights, and nonparametric bootstrap confidence intervals.

Version: 0.1.1
Depends: R (≥ 4.1.0)
Suggests: testthat (≥ 3.0.0)
Published: 2026-09-29
DOI: 10.32614/CRAN.package.accmv
Author: Gang Cheng [aut, cre], Yen-Chi Chen [aut], Maureen A. Smith [aut], Ying-Qi Zhao [aut]
Maintainer: Gang Cheng <mathchenggang at gmail.com>
BugReports: https://github.com/mathcg/ACCMV/issues
License: MIT + file LICENSE
URL: https://github.com/mathcg/ACCMV, https://arxiv.org/abs/2207.02289
NeedsCompilation: no
Citation: accmv citation info
CRAN checks: accmv results

Documentation:

Reference manual: accmv.html , accmv.pdf

Downloads:

Package source: accmv_0.1.1.tar.gz
Windows binaries: r-devel: accmv_0.1.1.zip, r-release: not available, r-oldrel: accmv_0.1.1.zip
macOS binaries: r-release (arm64): accmv_0.1.1.tgz, r-oldrel (arm64): accmv_0.1.1.tgz, r-release (x86_64): accmv_0.1.1.tgz, r-oldrel (x86_64): accmv_0.1.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=accmv to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.