The Ultimate Guide to the seqmon Package in R
Explore valuable documentation and insights to make the most of the seqmon package in R. Get ready to unlock the full potential of the seqmon package!
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What is the seqmon package?
In this section, we’ll delve into the fundamental aspects and key features of the package.
The seqmon package is designed to facilitate the monitoring of sequential trials in clinical research. It provides functions for adjusting stopping boundaries and assessing trial results, among other features, ensuring efficient and ethical operations of clinical trials.
- Title: Group Sequential Design Class for Clinical Trials
- Description: S4 class object for creating and managing group sequential designs. It calculates the efficacy and futility boundaries at each look. It allows modifying the design and tracking the design update history.
- Author: David A Schoenfeld and Hui Zheng
- Maintainer: Hui Zheng
How to install the seqmon package?
In this section, we’ll walk you through the process of installing and loading the seqmon 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 seqmon 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 seqmon 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 seqmon 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 seqmon package, visit our database of R package citations.
Technical details
- License type: MIT + file LICENSE. 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 seqmon package does not have compilation requirements.
- Required dependencies: A required dependency refers to another package that is essential for the functioning of the main package. The seqmon package has the following required dependencies: methods.
- Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The seqmon package has no suggested dependencies.
- External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The seqmon 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 seqmon package has no imported packages.
- Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The seqmon package has no enhancements.
How to get help with the seqmon package?
In this section, we’ll discuss a variety of available resources for getting help with the seqmon package.
Key resources
- The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("seqmon") 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 seqmon package does not have a dedicated website.
- Developer support: You can email Hui Zheng . For contact information, visit our R community directory.
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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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