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DTAT
View on CRAN: Click
here
Download and install DTAT package within the R console
Install from CRAN:
install.packages("DTAT")
Install from Github:
library("remotes")
install_github("cran/DTAT") Install by package version:
library("remotes")
install_version("DTAT", "0.3-8") Attach the package and use:
library("DTAT")
Maintained by
David C. Norris
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-02-18
Latest Update: 2025-07-24
Description:
Dose Titration Algorithm Tuning (DTAT) is a methodologic framework
allowing dose individualization to be conceived as a continuous
learning process that begins in early-phase clinical trials and
continues throughout drug development, on into clinical practice.
This package includes code that researchers may use to reproduce
or extend key results of the DTAT research programme, plus tools
for trialists to design and simulate a '3+3/PC' dose-finding study.
Please see Norris (2017a) and
Norris (2017c) .
How to cite:
David C. Norris (2019). DTAT: Dose Titration Algorithm Tuning. R package version 0.3-8, https://cran.r-project.org/web/packages/DTAT. Accessed 26 Aug. 2026.
Previous versions and publish date:
Other packages that cited DTAT R package
View DTAT citation profile
Other R packages that DTAT depends,
imports, suggests or enhances
Complete documentation for DTAT
Functions, R codes and Examples using
the DTAT R package
Some associated functions: DE-class . DTAT-package . Onoue.Friberg . as_d3_data-DE-method . de.bioRxiv.240846 . dose.survfit . dose.survival . ds.curve . dtat1000 . newton.raphson . plot-DE-missing-method . reexports . runDTATapp . scaled . seq.function . sim . titrate . titration .
Some associated R codes: AllClass.R . DTAT-internal.R . DTAT-package.R . Onoue.Friberg.R . dose.survfit.R . dose.survival.R . ds.curve.R . newton.raphson.R . reexports.R . runDTATapp.R . scaled.R . seq.function.R . titrate.R . Full DTAT package functions and examples
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