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DoseFinding (version 0.5-5)

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, fitting non-linear dose-response models, calculating optimal designs and an implementation of the MCPMod methodology.

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Version

Install

install.packages('DoseFinding')

Monthly Downloads

2,540

Version

0.5-5

License

GPL-3

Maintainer

Bjrn Bornkamp

Last Published

September 1st, 2011

Functions in DoseFinding (0.5-5)

getBnds

Calculates default bounds for non-linear parameters
modelMeans

Calculate mean vectors for a given candidate set
powerScenario

Calculates the power for an planMM object under a particular alternative scenario
AIC.DRMod

Calculate AIC, BIC or log-likelihood for a DRMod object
MCPMod

Perform MCPMod analysis of a data set
DoseFinding-internal

DoseFinding package internal functions
migraine

Migraine Dose Response data
DoseFinding-package

Package overview
IBScovars

Irritable Bowel Syndrome Dose Response data with covariates
bootMCPMod

Evaluate precision of dose estimate by nonparametric bootstrapping
MCPtest

Perform model-based multiple contrast test
gFitDRModel

Generalized fitting of dose-response models to raw dose-response estimates
fit.control

Set control parameters for non-linear model fitting
guesst

Calculate guesstimates based on prior knowledge
ED.DRMod

Calculate EDp estimator for a DRMod object
powerMM

Calculate power for different sample sizes
fullMod

Calculate location and scale parameters for candidate set of models
getInit

Starting values for non-linear parameters.
getPars

Calculate location and scale parameters
planMM

Calculate optimal contrasts and critical value for MCP test
getUpdDesign

Calculate Bayes estimates and optimal design for next cohort
MED.DRMod

Calculate MED for a DRMod object
critVal

Calculate critical value for multiple contrast test
plot.MCPMod

Plot MCPMod model fits
predict.MCPMod

Predict a MCPMod object.
plot.fullMod

Plot method for fullMod objects
LP

Sensitivity analysis for misspecification of standardized model parameters in MCPMod
Dose-Response Models

Built-in dose-response models in DoseFinding
sampSize

Sample size calculations for MCPMod
rndDesign

Round a continuous design to integer values.
calcBayesEst

Calculates posterior estimates and posterior model probabilities for a set of candidate models.
calcCrit

Calculate design criterion for a specified design.
fitDRModel

Fit a non-linear regression model with linear covariates.
mvtnorm.control

Control options for pmvt and qmvt functions
plot.powerMM

Plot method for powerMM objects
biom

Biometrics Dose Response data
genDFdata

Simulate dose-response data
calcOptDesign

Function to calculate an optimal design
DRMod and gDRMod methods

Methods for DRMod and gDRMod objects
powCalc

Calculate the power for the multiple contrast test
gMCPtest

Generalized multiple contrast tests
getGrad

Calculate the gradient for the non-linear part of a DRMod object
plot.LP

Plot method for LP objects
plotModels

Plot candidate models
plot.planMM

Plotting a planMM object