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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>.

Version: 2.1
Depends: R (≥ 3.5.0)
Imports: stats
Published: 2022-01-04
Author: Paul R. Rosenbaum
Maintainer: Paul R. Rosenbaum <rosenbaum at wharton.upenn.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: sensitivitymw results

Documentation:

Reference manual: sensitivitymw.pdf

Downloads:

Package source: sensitivitymw_2.1.tar.gz
Windows binaries: r-devel: sensitivitymw_2.1.zip, r-release: sensitivitymw_2.1.zip, r-oldrel: sensitivitymw_2.1.zip
macOS binaries: r-release (arm64): sensitivitymw_2.1.tgz, r-oldrel (arm64): sensitivitymw_2.1.tgz, r-release (x86_64): sensitivitymw_2.1.tgz, r-oldrel (x86_64): sensitivitymw_2.1.tgz
Old sources: sensitivitymw archive

Reverse dependencies:

Reverse suggests: senstrat, tailTransform, weightedRank

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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