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This repository has been archived by the owner on Aug 31, 2022. It is now read-only.
Hello {gMCPmini} team! @dong-xi and I are working on a similar initiative to {gMCPmini}, namely extending the library with:
a general testing strategy that allows a mixture of test types (Bonferroni, parametric, Simes)
optimal graphs
entangled graphs
We'd love to contribute to your project if possible! I'm working on migrating calcPower() from {gMCP} and setting up the requisite unit tests with {testthat} so I'd be happy to submit a PR and perhaps we can have a discussion about how to collaborate.
The text was updated successfully, but these errors were encountered:
Thanks @samussiah for asking to contribute! PR is always welcome 🤝
Just a little bit history of this small package initiation and development. The gMCPmini package is initially developed to reduce the Java dependency, so it can be compatible with organization's restricted operating system. Later on, we migrated and modified most graphical setting and testing related functions from original gMCP package, and added a ggplot2-based flexible graphical function. We also restructured the package and added formal testing cases with testthat. Based on these focus, we did not touch the functions related to power calculation, simulation, extensive graph such as entangled graph, etc. So your proposal will surely be nice complements of this package.
FYI, potentially this repo could be moved under Merck's Github account. We can discuss what is a better way to collaborate. 😄
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Hello {gMCPmini} team! @dong-xi and I are working on a similar initiative to {gMCPmini}, namely extending the library with:
We'd love to contribute to your project if possible! I'm working on migrating
calcPower()
from{gMCP}
and setting up the requisite unit tests with{testthat}
so I'd be happy to submit a PR and perhaps we can have a discussion about how to collaborate.The text was updated successfully, but these errors were encountered: