Package: DoseFinding 1.2-1

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], Novartis Pharma AG [cph, fnd]

DoseFinding_1.2-1.tar.gz
DoseFinding_1.2-1.tar.gz(r-4.5-noble)DoseFinding_1.2-1.tar.gz(r-4.4-noble)
DoseFinding_1.2-1.tgz(r-4.4-emscripten)DoseFinding_1.2-1.tgz(r-4.3-emscripten)
DoseFinding.pdf |DoseFinding.html✨
DoseFinding/json (API)
NEWS

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

Peer review:

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

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

7.31 score 10 packages 93 scripts 1.5k downloads 8 mentions 47 exports 29 dependencies

Last updated 2 months agofrom:33695fc9b9. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 23 2024
R-4.5-linux-x86_64OKOct 23 2024

Exports:betaModbetaModGradbFitModbMCTtestcalcCritcritValdefBndsDesignMCPModAppEDemaxemaxGradexponentialexponentialGradfitModgAICgetRespguesstlinearlinearGradlinIntlinIntGradlinloglinlogGradlogisticlogisticGradMCPModMCTpvalMCTtestModsmvpostmixmvtnorm.controloptControptDesignplanModplotContrplotModspowMCTpowNquadraticquadraticGradrndDesignsampSizesampSizeMCTsigEmaxsigEmaxGradtargNTD

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr

Continuous data MCP-Mod

Rendered fromanalysis_normal.Rmdusingknitr::rmarkdownon Oct 23 2024.

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

Multiple Regimen MCP-Mod

Rendered frommult_regimen.Rmdusingknitr::rmarkdownon Oct 23 2024.

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

Binary Data MCP-Mod

Rendered frombinary_data.Rmdusingknitr::rmarkdownon Oct 23 2024.

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

MCP-Mod FAQ

Rendered fromfaq.Rmdusingknitr::rmarkdownon Oct 23 2024.

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

Overview DoseFinding package

Rendered fromoverview.Rmdusingknitr::rmarkdownon Oct 23 2024.

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

Sample size calculations for MCP-Mod

Rendered fromsample_size.Rmdusingknitr::rmarkdownon Oct 23 2024.

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
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
Sample size calculationsplot.targN powN sampSize sampSizeMCT targN
Calculate dose estimates for a fitted dose-response model (via 'fitMod' or 'bFitMod') or a 'Mods' objectED Target doses TD