Package: evidenceFactors 1.8

Bikram Karmakar

evidenceFactors: Reporting Tools for Sensitivity Analysis of Evidence Factors in Observational Studies

Provides tools for integrated sensitivity analysis of evidence factors in observational studies. When an observational study allows for multiple independent or nearly independent inferences which, if vulnerable, are vulnerable to different biases, we have multiple evidence factors. This package provides methods that respect type I error rate control. Examples are provided of integrated evidence factors analysis in a longitudinal study with continuous outcome and in a case-control study. Karmakar, B., French, B., and Small, D. S. (2019)<doi:10.1093/biomet/asz003>.

Authors:Bikram Karmakar

evidenceFactors_1.8.tar.gz
evidenceFactors_1.8.tar.gz(r-4.5-noble)evidenceFactors_1.8.tar.gz(r-4.4-noble)
evidenceFactors_1.8.tgz(r-4.4-emscripten)evidenceFactors_1.8.tgz(r-4.3-emscripten)
evidenceFactors.pdf |evidenceFactors.html
evidenceFactors/json (API)

# Install 'evidenceFactors' in R:
install.packages('evidenceFactors', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • Gamlist - Gamma list for illustration of the use of the package.
  • Plist - P-value list for illustration of the use of the package.
  • mtm - DNA damage from exposure to chromium

On CRAN:

Conda-Forge:

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

1.00 score 5 scripts 150 downloads 3 exports 1 dependencies

Last updated 5 years agofrom:83cb32d18c. Checks:2 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 25 2025
R-4.5-linuxOKFeb 25 2025

Exports:plotRejDecbyAssmplotRetentionArearetentionBrd

Dependencies:sensitivitymv