The Ultimate Guide to the c212 Package in R
Explore valuable documentation and insights to make the most of the c212 package in R. Get ready to unlock the full potential of the c212 package!
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What is the c212 package?
In this section, we’ll delve into the fundamental aspects and key features of the package.
c212 is an R package that provides a set of tools for conducting phase I and II clinical trials with adaptive designs. This includes functions for simulating trial outcomes, calculating optimal dose levels, and performing other tasks common in clinical trials.
- Title: Methods for Detecting Safety Signals in Clinical Trials Using Body-Systems (System Organ Classes)
- Description: Methods for detecting safety signals in clinical trials using groupings of adverse events by body-system or system organ class. This work was supported by the Engineering and Physical Sciences Research Council (UK) (EPSRC) [award reference 1521741] and Frontier Science (Scotland) Ltd. The package title c212 is in reference to the original Engineering and Physical Sciences Research Council (UK) funded project which was named CASE 2/12.
- Author: Raymond Carragher [aut, cre] ()
- Maintainer: Raymond Carragher
How to install the c212 package?
In this section, we’ll walk you through the process of installing and loading the c212 package. By following these steps, you can seamlessly add new functions, datasets, and other resources to your R environment for a more robust workflow.
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What package information should you know?
In this section, we’ll go over the technical aspects of the c212 package.
Key features
- Datasets: Many R packages include built-in datasets that you can use to familiarize yourself with their functionalities. To identify built-in datasets. To identify the datasets for the c212 package, visit our database of R datasets.
- Vignettes: R vignettes are documents that include examples for using a package. To view the list of available vignettes for the c212 package, you can visit our visit our database of R vignettes.
- Citation: Citing R packages in your publications is important as it recognizes the contributions of the developers. To find citation information for the c212 package, visit our database of R package citations.
Technical details
- License type: GPL (>= 2). For license details, visit the Open Source Initiative website.
- Compilation requirements: Some R packages include internal code that must be compiled for them to function correctly. The c212 package has compilation requirements.
- Required dependencies: A required dependency refers to another package that is essential for the functioning of the main package. The c212 package has the following required dependencies: coda.
- Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The c212 package has no suggested dependencies.
- External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The c212 package does not use any external sources.
- Imported packages: Importing packages allows developers to leverage existing code and functionalities without having to reinvent the wheel. The c212 package has no imported packages.
- Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The c212 package has no enhancements.
How to get help with the c212 package?
In this section, we’ll discuss a variety of available resources for getting help with the c212 package.
Key resources
- The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("c212") function to retrieve detailed information, examples, and usage instructions. Alternatively, you can use the ? operator as a shortcut.
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Package website: The c212 package does not have a dedicated website.
- Developer support: You can email Raymond Carragher . For contact information, visit our R community directory.
Additional resources
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- Discussion forums: Online forums are excellent platforms to ask questions, share knowledge, and troubleshoot issues. The most popular forums for R programmers are StackOverflow and Posit Community.
Other package guides
Explore our comprehensive guides for other R packages. These guides are valuable resources for accessing a wide range of information, making it easier to navigate R documentation in one place.
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