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-4.5)PINMA_1.1-2.zip(r-4.4)PINMA_1.1-2.zip(r-4.3)
PINMA_1.1-2.tgz(r-4.4-any)PINMA_1.1-2.tgz(r-4.3-any)
PINMA_1.1-2.tar.gz(r-4.5-noble)PINMA_1.1-2.tar.gz(r-4.4-noble)
PINMA_1.1-2.tgz(r-4.4-emscripten)PINMA_1.1-2.tgz(r-4.3-emscripten)
PINMA.pdf |PINMA.html
PINMA/json (API)
NEWS

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

Peer review:

Datasets:
  • dstr - Siontis et al. (2018)'s network meta-analysis data

On CRAN:

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

4 exports 0.00 score 9 dependencies 185 downloads

Last updated 1 years agofrom:47e899579a. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 20 2024
R-4.5-winOKAug 20 2024
R-4.5-linuxOKAug 20 2024
R-4.4-winOKAug 20 2024
R-4.4-macOKAug 20 2024
R-4.3-winOKAug 20 2024
R-4.3-macOKAug 20 2024

Exports:data.editKRPBStPI

Dependencies:latticeMASSmathjaxrMatrixmetadatmetafornlmenumDerivpbapply