Package: sensitivitymw 2.1

sensitivitymw: Sensitivity Analysis for Observational Studies Using Weighted M-Statistics

Sensitivity analysis for tests, confidence intervals and estimates in matched observational studies with one or more controls using weighted or unweighted Huber-Maritz M-tests (including the permutational t-test). The method is from Rosenbaum (2014) Weighted M-statistics with superior design sensitivity in matched observational studies with multiple controls JASA, 109(507), 1145-1158 <doi:10.1080/01621459.2013.879261>.

Authors:Paul R. Rosenbaum

sensitivitymw_2.1.tar.gz
sensitivitymw_2.1.zip(r-4.7)sensitivitymw_2.1.zip(r-4.6)sensitivitymw_2.1.zip(r-4.5)
sensitivitymw_2.1.tgz(r-4.6-any)sensitivitymw_2.1.tgz(r-4.5-any)
sensitivitymw_2.1.tar.gz(r-4.7-any)sensitivitymw_2.1.tar.gz(r-4.6-any)
sensitivitymw_2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
sensitivitymw/json (API)

# Install 'sensitivitymw' in R:
install.packages('sensitivitymw', repos = c('https://rosenbap.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • erpcp - DNA Damage Among Welders
  • mercury - NHANES Mercury/Fish Data

On CRAN:

Conda:

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

1.60 score 1 stars 40 scripts 265 downloads 6 exports 0 dependencies

Last updated from:c29739154c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK144
source / vignettesOK148
linux-release-x86_64OK119
macos-release-arm64OK113
macos-oldrel-arm64OK84
windows-develOK60
windows-releaseOK63
windows-oldrelOK122
wasm-releaseOK97

Exports:mscorevmultrnksnewurkssenmwsenmwCIseparable1k

Dependencies: