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README.Rmd
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---
output: github_document
bibliography: "`r system.file('references.bib', package='graphicalMCP')`"
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
results = "hide",
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
fig.align = "center"
)
```
<!-- badges: start -->
[](https://www.repostatus.org/#active)
[](https://cran.r-project.org/package=graphicalMCP)
[](https://cranlogs.r-pkg.org/badges/graphicalMCP)
[](https://cranlogs.r-pkg.org/badges/grand-total/graphicalMCP)
<!-- [](https://openpharma.github.io/graphicalMCP/latest-tag/coverage-report/) -->
<!-- badges: end -->
# graphicalMCP <a href="https://openpharma.github.io/graphicalMCP/"><img src="man/figures/logo.png" align="right" height="139" /></a>
# Introduction
Graphical approaches for multiple comparison procedures (MCPs) are a general framework to control the family-wise error rate strongly at a pre-specified significance level $0<\alpha<1$. This approach includes many commonly used MCPs as special cases and is transparent in visualizing MCPs for better communications. `graphicalMCP` is designed to design and analyze graphical MCPs in a flexible, informative and efficient way.
# Installation
### Release
You can install the current release version from *CRAN* with:
```{r cran-installation, eval = FALSE}
install.packages("graphicalMCP")
```
### Development
You can install the current development version from *GitHub* with:
```{r github-installation, eval = FALSE}
# install.packages("pak")
pak::pak("openpharma/graphicalMCP")
```
# Documentation
- For basic usage instructions, see `vignette("graphicalMCP")`
- To become familiar with graphical MCP terminologies, see `vignette("glossary")`
- To learn examples of how to use `graphicalMCP`,
- see `vignette("shortcut-testing")` for sequentially rejective graphical multiple comparison procedures based on Bonferroni tests
- see `vignette("closed-testing")` for graphical multiple comparison procedures based on the closure principle
- see `vignette("graph-examples")` for common multiple comparison procedures illustrated using `graphicalMCP`
- see `vignette("generate-closure")` for rationales to generate the closure and the weighting strategy of a graph
- see `vignette("comparisons")` for comparisons to other R packages
- To view vignettes in R after properly installing `graphicalMCP`, we can build vignettes by `devtools::install(build_vignettes = TRUE)`, and then use `browseVignettes("graphicalMCP")` to view the full list of vignettes
# Related work
- Graphical MCPs - [gMCP](https://cran.r-project.org/package=gMCP)
- Lighter version of `gMCP` which removes the rJava dependency - [gMCPLite](https://cran.r-project.org/package=gMCPLite)
- Graphical MCPs with Simes tests - [lrstat](https://cran.r-project.org/package=lrstat)
Built upon these packages, we hope to implement graphical MCPs in a more general framework, with fewer dependencies and simpler S3 classes, and without losing computational efficiency.
# Acknowledgments
Along with the authors and contributors, thanks to the following people for their suggestions and inspirations on the package:
Frank Bretz, Willi Maurer, Ekkehard Glimm, Nan Chen, Jeremy Wildfire, Spencer Childress, Colleen McLaughlin, Matt Roumaya, Chelsea Dickens, Nan Xiao, Keaven Anderson, and Ron Yu
We owe a debt of gratitude to the authors of [gMCP](https://cran.r-project.org/package=gMCP) for their pioneering work, without which this package would not be nearly as extensive as it is.