Package: DoseFinding 1.4-1

Marius Thomas

DoseFinding: Planning and Analyzing Dose Finding Experiments

The DoseFinding package provides functions for the design and analysis of dose-finding experiments (with focus on pharmaceutical Phase II clinical trials). It provides functions for: multiple contrast tests, fitting non-linear dose-response models (using Bayesian and non-Bayesian estimation), calculating optimal designs and an implementation of the MCPMod methodology (Pinheiro et al. (2014) <doi:10.1002/sim.6052>).

Authors:Bjoern Bornkamp [aut], Jose Pinheiro [aut], Frank Bretz [aut], Ludger Sandig [aut], Marius Thomas [aut, cre], Daniel Sabanes Bove [aut], Novartis Pharma AG [cph, fnd]

DoseFinding_1.4-1.tar.gz
DoseFinding_1.4-1.tar.gz(r-4.7-arm64)DoseFinding_1.4-1.tar.gz(r-4.7-x86_64)DoseFinding_1.4-1.tar.gz(r-4.6-arm64)DoseFinding_1.4-1.tar.gz(r-4.6-x86_64)
DoseFinding_1.4-1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
DoseFinding/json (API)
NEWS

# Install 'DoseFinding' in R:
install.packages('DoseFinding', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/openpharma/dosefinding/issues

Pkgdown/docs site:https://openpharma.github.io

Uses libs:
  • openblas– Optimized BLAS
Datasets:
  • biom - Biometrics Dose Response data
  • glycobrom - Glycopyrronium Bromide dose-response data
  • IBScovars - Irritable Bowel Syndrome Dose Response data with covariates
  • migraine - Migraine Dose Response data
  • neurodeg - Neurodegenerative disease simulated longitudinal dose-finding data set

On CRAN:

Conda:

openblas

7.85 score 9 packages 137 scripts 6.8k downloads 8 mentions 49 exports 19 dependencies

Last updated from:0e4e9aa9c8. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK240
linux-devel-x86_64OK233
source / vignettesOK393
linux-release-arm64OK241
linux-release-x86_64OK261
wasm-releaseOK147

Exports:betaModbetaModGradbFitModbMCTtestcalcCritcritValdefBndsDesignMCPModAppEDemaxemaxGradexponentialexponentialGradfitModgAICgetRespguesstlinearlinearGradlinIntlinIntGradlinloglinlogGradlogisticlogisticGradmaFitModMCPModMCTpvalMCTtestModsmvpostmixmvtnorm.controloptControptDesignplanModplotContrplotModspowMCTpowMCTInterimpowNquadraticquadraticGradrndDesignsampSizesampSizeMCTsigEmaxsigEmaxGradtargNTD

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglatticelifecyclemvtnormR6RColorBrewerrlangS7scalesvctrsviridisLitewithr

Continuous data MCP-Mod

Rendered fromanalysis_normal.Rmdusingknitr::rmarkdownon Jun 04 2026.

Last update: 2025-03-11
Started: 2021-06-25

Multiple Regimen MCP-Mod

Rendered frommult_regimen.Rmdusingknitr::rmarkdownon Jun 04 2026.

Last update: 2024-08-24
Started: 2021-06-25

Binary Data MCP-Mod

Rendered frombinary_data.Rmdusingknitr::rmarkdownon Jun 04 2026.

Last update: 2025-07-09
Started: 2021-06-25

Longitudinal Data MCP-Mod

Rendered fromlongitudinal_data.Rmdusingknitr::rmarkdownon Jun 04 2026.

Last update: 2025-07-09
Started: 2025-07-09

MCP-Mod FAQ

Rendered fromfaq.Rmdusingknitr::rmarkdownon Jun 04 2026.

Last update: 2024-08-24
Started: 2021-06-25

Overview DoseFinding package

Rendered fromoverview.Rmdusingknitr::rmarkdownon Jun 04 2026.

Last update: 2024-08-24
Started: 2021-06-25

Sample size calculations for MCP-Mod

Rendered fromsample_size.Rmdusingknitr::rmarkdownon Jun 04 2026.

Last update: 2024-08-24
Started: 2021-06-25

Readme and manuals

Help Manual

Help pageTopics
Fit a dose-response model using Bayesian or bootstrap methods.bFitMod coef.bFitMod plot.bFitMod predict.bFitMod
Biometrics Dose Response databiom
Performs Bayesian multiple contrast testbMCTtest
Calculate critical value for multiple contrast testcritVal
Calculates default bounds for non-linear parameters in dose-response modelsdefBnds
Start externally hosted DesignMCPMod Shiny AppDesignMCPModApp
Built-in dose-response models in DoseFindingbetaMod betaModGrad drmodels emax emaxGrad exponential exponentialGrad linear linearGrad linInt linIntGrad linlog linlogGrad logistic logisticGrad quadratic quadraticGrad sigEmax sigEmaxGrad
Fit non-linear dose-response modelAIC.DRMod coef.DRMod fitMod gAIC gAIC.DRMod logLik.DRMod plot.DRMod predict.DRMod vcov.DRMod
Glycopyrronium Bromide dose-response dataglycobrom
Calculate guesstimates based on prior knowledgeguesst
Irritable Bowel Syndrome Dose Response data with covariatesIBScovars
Fit dose-response models via bootstrap model averaging (bagging)maFitMod plot.maFit predict.maFit print.maFit
MCPMod - Multiple Comparisons and ModelingMCPMod plot.MCPMod predict.MCPMod
Calculate multiplicity adjusted p-values for multiple contrast testMCTpval
Performs multiple contrast testMCTtest
Migraine Dose Response datamigraine
Define dose-response modelsgetResp Mods plot.Mods plotMods
Prior to posterior updating for a multivariate normal mixturemvpostmix
Control options for pmvt and qmvt functionsmvtnorm-control mvtnorm.control
Neurodegenerative disease simulated longitudinal dose-finding data setneurodeg
Calculate optimal contrastsoptContr plot.optContr plotContr
Function to calculate optimal designscalcCrit optDesign plot.DRdesign rndDesign
Evaluate performance metrics for fitting dose-response modelsplanMod plot.planMod summary.planMod
Calculate power for multiple contrast testpowMCT
Calculate Conditional or Predictive Power for Multiple Contrast TestpowMCTInterim
Sample size calculationsplot.targN powN sampSize sampSizeMCT targN
Calculate dose estimates for a fitted dose-response model (via 'fitMod()', 'bFitMod()') or 'maFitMod()') or a 'Mods()' objectED Target doses TD