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multfisher  

Optimal Exact Tests for Multiple Binary Endpoints
View on CRAN: Click here


Download and install multfisher package within the R console
Install from CRAN:
install.packages("multfisher")

Install from Github:
library("remotes")
install_github("cran/multfisher")

Install by package version:
library("remotes")
install_version("multfisher", "1.1")



Attach the package and use:
library("multfisher")
Maintained by
Robin Ristl
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-04-27
Latest Update: 2018-02-23
Description:
Calculates exact hypothesis tests to compare a treatment and a reference group with respect to multiple binary endpoints. The tested null hypothesis is an identical multidimensional distribution of successes and failures in both groups. The alternative hypothesis is a larger success proportion in the treatment group in at least one endpoint. The tests are based on the multivariate permutation distribution of subjects between the two groups. For this permutation distribution, rejection regions are calculated that satisfy one of different possible optimization criteria. In particular, regions with maximal exhaustion of the nominal significance level, maximal power under a specified alternative or maximal number of elements can be found. Optimization is achieved by a branch-and-bound algorithm. By application of the closed testing principle, the global hypothesis tests are extended to multiple testing procedures.
How to cite:
Robin Ristl (2017). multfisher: Optimal Exact Tests for Multiple Binary Endpoints. R package version 1.1, https://cran.r-project.org/web/packages/multfisher. Accessed 04 Aug. 2026.
Previous versions and publish date:
(2026-07-09 06:33), 1.0 (2017-04-27 18:14)
Other packages that cited multfisher R package
View multfisher citation profile
Other R packages that multfisher depends, imports, suggests or enhances
Complete documentation for multfisher
Functions, R codes and Examples using the multfisher R package
Some associated functions: mfisher.test . plot.multfisher . print.multfisher . 
Some associated R codes: multBinExact_2-4.R .  Full multfisher package functions and examples
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