The Ultimate Guide to the tLagInterim Package in R
Explore valuable documentation and insights to make the most of the tLagInterim package in R. Get ready to unlock the full potential of the tLagInterim package!
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What is the tLagInterim package?
In this section, we’ll delve into the fundamental aspects and key features of the package.
The tLagInterim package provides tools for time-lagged interim analyses in clinical trials. This package offers functions to estimate the sample size and statistical power for time-lagged interim analyses, offering a valuable tool for clinical trial design and analysis.
- Title: Interim Monitoring of Clinical Trials with Time-Lagged Outcome
- Description: Implements inverse and augmented inverse probability weighted estimators for common treatment effect parameters at an interim analysis with time-lagged outcome that may not be available for all enrolled subjects. Produces estimators, standard errors, and information that can be used to compute stopping boundaries using software that assumes that the estimators/test statistics have independent increments. Tsiatis, A. A. and Davidian, M., (2022) .
- Author: Shannon T. Holloway [aut, cre], Marie Davidian [aut], Anastasios Tsiatis [aut]
- Maintainer: Shannon T. Holloway
How to install the tLagInterim package?
In this section, we’ll walk you through the process of installing and loading the tLagInterim 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 tLagInterim 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 tLagInterim 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 tLagInterim 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 tLagInterim 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 tLagInterim 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 tLagInterim package has the following required dependencies: R (>= 3.5.0), survival.
- Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The tLagInterim package has no suggested dependencies.
- External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The tLagInterim 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 tLagInterim package has the following imported packages: R.utils.
- Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The tLagInterim package has no enhancements.
How to get help with the tLagInterim package?
In this section, we’ll discuss a variety of available resources for getting help with the tLagInterim package.
Key resources
- The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("tLagInterim") 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 tLagInterim package does not have a dedicated website.
- Developer support: You can email Shannon T. Holloway . 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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