DoseFinding-package: DoseFinding: Planning and Analyzing Dose Finding Experiments

In DoseFinding: Planning and Analyzing Dose Finding Experiments

DoseFinding: Planning and Analyzing Dose Finding Experiments

Description

The DoseFinding package provides functions for the design and analysis of dose-finding experiments (for example pharmaceutical Phase II clinical trials). It provides functions for: multiple contrast tests (MCTtest), fitting non-linear dose-response models (fitMod), a combination of testing and dose-response modelling (MCPMod), and calculating optimal designs (optDesign), both for normal and general response variable.

Details

The main functions are:
MCTtest: Implements a multiple contrast tests
powMCT: Power calculations for multiple contrast tests
fitMod: Fits non-linear dose-response models
optDesign: Calculates optimal designs for dose-response models
MCPMod: Performs MCPMod methodology
sampSize: General function for sample size calculation

Author(s)

Maintainer: Marius Thomas [e-mail]

Authors:

• Bjoern Bornkamp [e-mail] (ORCID)

• Jose Pinheiro

• Frank Bretz

• Ludger Sandig

• Daniel Sabanes Bove [e-mail] (ORCID)

Other contributors:

• Novartis Pharma AG [copyright holder, funder]

References

\insertRef

bornkamp2011DoseFinding

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bornkamp2009DoseFinding

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bretz2005DoseFinding

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dette2008DoseFinding

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oquigley2017DoseFinding

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pinheiro2006DoseFinding

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pinheiro2014DoseFinding

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seber2003DoseFinding

See Also

Useful links:

• https://github.com/openpharma/DoseFinding

• https://openpharma.github.io/DoseFinding/

• Report bugs at https://github.com/openpharma/DoseFinding/issues

Examples

data(IBScovars)

## perform (model based) multiple contrast test
## define candidate dose-response shapes
models <- Mods(linear = NULL, emax = 0.2, quadratic = -0.17,
               doses = c(0, 1, 2, 3, 4))
## plot models
plot(models)
## perform multiple contrast test
test <- MCTtest(dose, resp, IBScovars, models=models,
                addCovars = ~ gender)

## fit non-linear emax dose-response model
fitemax <- fitMod(dose, resp, data=IBScovars, model="emax",
                  bnds = c(0.01,5))
## display fitted dose-effect curve
plot(fitemax, CI=TRUE, plotData="meansCI")

## Calculate optimal designs for target dose (TD) estimation
doses <- c(0, 10, 25, 50, 100, 150)
fmodels <- Mods(linear = NULL, emax = 25, exponential = 85,
                logistic = c(50, 10.8811),
                doses = doses, placEff=0, maxEff=0.4)
plot(fmodels, plotTD = TRUE, Delta = 0.2)
weights <- rep(1/4, 4)
desTD <- optDesign(fmodels, weights, Delta=0.2, designCrit="TD")

DoseFinding documentation built on Oct. 16, 2026, 5:08 p.m.