Package: meta.shrinkage 0.1.4

Nanami Taketomi

meta.shrinkage: Meta-Analyses for Simultaneously Estimating Individual Means

Implement meta-analyses for simultaneously estimating individual means with shrinkage, isotonic regression and pretests. Include our original implementation of the isotonic regression via the pool-adjacent-violators algorithm (PAVA) algorithm. For the pretest estimator, the confidence interval for individual means are provided. Methodologies were published in Taketomi et al. (2021) <doi:10.3390/axioms10040267>, Taketomi et al. (2022) <doi:10.3390/a15010026>, Taketomi et al. (2023-) (under review).

Authors:Nanami Taketomi, Takeshi Emura

meta.shrinkage_0.1.4.tar.gz
meta.shrinkage_0.1.4.tar.gz(r-4.5-noble)meta.shrinkage_0.1.4.tar.gz(r-4.4-noble)
meta.shrinkage_0.1.4.tgz(r-4.4-emscripten)meta.shrinkage_0.1.4.tgz(r-4.3-emscripten)
meta.shrinkage.pdf |meta.shrinkage.html
meta.shrinkage/json (API)

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

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

4 exports 6.14 score 0 dependencies 706 mentions 412 downloads

Last updated 1 years agofrom:65d3622f36. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 26 2024
R-4.5-linuxOKAug 26 2024

Exports:gptjsrjsrml

Dependencies: