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) <doi:10.12688/f1000research.10624.3> and Norris (2017c) <doi:10.1101/240846>.
Version: 0.3-7 Depends: R (≥ 3.5.0), survival Imports: km.ci, pomp, Hmisc, data.table, dplyr, r2d3, shiny, jsonlite, methods Suggests: knitr, rmarkdown, lattice, latticeExtra, widgetframe, tidyr, RColorBrewer, invgamma, zipfR, rms Published: 2024-05-25 DOI: 10.32614/CRAN.package.DTAT Author: David C. Norris [aut, cre] Maintainer: David C. Norris <david at precisionmethods.guru> License: MIT + file LICENSE URL: https://precisionmethods.guru/ NeedsCompilation: no Citation: DTAT citation info In views: ClinicalTrials CRAN checks: DTAT results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=DTAT to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4