The Ultimate Guide to the escalation Package in R

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Explore valuable documentation and insights to make the most of the escalation package in R. Get ready to unlock the full potential of the escalation package!

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What is the escalation package?

In this section, we’ll delve into the fundamental aspects and key features of the package.

escalation is an R package that provides tools for designing dose escalation trials, which are used in the early phases of clinical drug development. It includes functions for defining trial parameters, simulating trial outcomes, and analyzing trial data.

Title: Modular Approach to Dose Finding Clinical Trials
Description: Methods for working with dose-finding clinical trials. We provide implementations of many dose-finding clinical trial designs, including the continual reassessment method (CRM) by O'Quigley et al. (1990) , the toxicity probability interval (TPI) design by Ji et al. (2007) , the modified TPI (mTPI) design by Ji et al. (2010) , the Bayesian optimal interval design (BOIN) by Liu & Yuan (2015) , EffTox by Thall & Cook (2004) ; the design of Wages & Tait (2015) , and the 3+3 described by Korn et al. (1994) . All designs are implemented with a common interface. We also offer optional additional classes to tailor the behaviour of all designs, including avoiding skipping doses, stopping after n patients have been treated at the recommended dose, stopping when a toxicity condition is met, or demanding that n patients are treated before stopping is allowed. By daisy-chaining together these classes using the pipe operator from 'magrittr', it is simple to tailor the behaviour of a dose-finding design so it behaves how the trialist wants. Having provided a flexible interface for specifying designs, we then provide functions to run simulations and calculate dose-paths for future cohorts of patients.
Author: Kristian Brock [aut, cre] (), Daniel Slade [ctb] ()
Maintainer: Kristian Brock

How to install the escalation package?

In this section, we’ll walk you through the process of installing and loading the escalation package. By following these steps, you can seamlessly add new functions, datasets, and other resources to your R environment for a more robust workflow.

# Install the {Package} package if it's not already installed
if (!require("{Package}")) {
    install.packages("{Package}")
}


# Load the {Package} package
library("{Package}")

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What package information should you know?

In this section, we’ll go over the technical aspects of the escalation 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 escalation 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 escalation 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 escalation package, visit our database of R package citations.

Technical details

License type: GPL (>= 3). 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 escalation 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 escalation package has the following required dependencies: magrittr.
Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The escalation package has the following suggested dependencies: testthat, knitr, rmarkdown, ggplot2, covr.
External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The escalation 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 escalation package has the following imported packages: dplyr, tidyr (>= 1.0), tidyselect, stringr, purrr, tibble, gtools, dfcrm, BOIN, trialr (>= 0.1.5), DiagrammeR, RColorBrewer, viridis, binom.
Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The escalation package has no enhancements.

How to get help with the escalation package?

In this section, we’ll discuss a variety of available resources for getting help with the escalation package.

Key resources

The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("escalation") function to retrieve detailed information, examples, and usage instructions. Alternatively, you can use the ? operator as a shortcut.
Package website: The escalation package does not have a dedicated website.
Developer support: You can email Kristian Brock . For contact information, visit our R community directory.

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Other package guides

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