Package: PINMA 1.1-2

PINMA: Improved Methods for Constructing Prediction Intervals for Network Meta-Analysis

Improved methods to construct prediction intervals for network meta-analysis. The parametric bootstrap and Kenward-Roger-type adjustment by Noma et al. (2022) <forthcoming> are implementable.

Authors:Hisashi Noma [aut, cre]

PINMA_1.1-2.tar.gz
PINMA_1.1-2.zip(r-4.7)PINMA_1.1-2.zip(r-4.6)PINMA_1.1-2.zip(r-4.5)
PINMA_1.1-2.tgz(r-4.6-any)PINMA_1.1-2.tgz(r-4.5-any)
PINMA_1.1-2.tar.gz(r-4.7-any)PINMA_1.1-2.tar.gz(r-4.6-any)
PINMA_1.1-2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
PINMA/json (API)

# Install 'PINMA' in R:
install.packages('PINMA', repos = c('https://nomahi.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • dstr - Siontis et al. (2018)'s network meta-analysis data

On CRAN:

Conda:

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

1.00 score 194 downloads 4 exports 10 dependencies

Last updated from:47e899579a. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK164
source / vignettesOK144
linux-release-x86_64OK160
macos-release-arm64OK87
macos-oldrel-arm64OK119
windows-develOK85
windows-releaseOK82
windows-oldrelOK74
wasm-releaseOK112

Exports:data.editKRPBStPI

Dependencies:digestlatticeMASSmathjaxrMatrixmetadatmetafornlmenumDerivpbapply