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DoseFinding (version 0.6-3)

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

0.6-3

License

GPL-3

Maintainer

Bjrn Bornkamp

Last Published

August 22nd, 2012

Functions in DoseFinding (0.6-3)

plot.MCPMod

Plot MCPMod model fits
fit.control

Set control parameters for non-linear model fitting
DoseFinding-package

Package overview
genDFdata

Simulate dose-response data
getUpdDesign

Calculate Bayes estimates and optimal design for next cohort
plot.powerMM

Plot method for powerMM objects
calcCrit

Calculate design criterion for a specified design.
plotModels

Plot candidate models
powerMM

Calculate power for different sample sizes
biom

Biometrics Dose Response data
plot.fullMod

Plot method for fullMod objects
DR-Models

Built-in dose-response models in DoseFinding
MCPtest

Perform model-based multiple contrast test
critVal

Calculate critical value for multiple contrast test
MED.DRMod

Calculate MED for a DRMod object
modelMeans

Calculate mean vectors for a given candidate set
plot.planMM

Plotting a planMM object
powerScenario

Calculates the power for an planMM object under a particular alternative scenario
getInit

Starting values for non-linear parameters.
getPars

Calculate location and scale parameters
bootMCPMod

Evaluate precision of dose estimate by nonparametric bootstrapping
rndDesign

Round a continuous design to integer values.
AIC.DRMod

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

Function to calculate an optimal design
IBScovars

Irritable Bowel Syndrome Dose Response data with covariates
ED.DRMod

Calculate EDp estimator for a DRMod object
LP

Sensitivity analysis for misspecification of standardized model parameters in MCPMod
gMCPtest

Generalized multiple contrast tests
MCPMod

Perform MCPMod analysis of a data set
migraine

Migraine Dose Response data
powCalc

Calculate the power for the multiple contrast test
getBnds

Calculates default bounds for non-linear parameters
fitDRModel

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

Control options for pmvt and qmvt functions
gFitDRModel

Generalized fitting of dose-response models to raw dose-response estimates
planMM

Calculate optimal contrasts and critical value for MCP test
plot.LP

Plot method for LP objects
guesst

Calculate guesstimates based on prior knowledge
DoseFinding-internal

DoseFinding package internal functions
calcBayesEst

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

Predict a MCPMod object.
DRMod and gDRMod methods

Methods for DRMod and gDRMod objects
fullMod

Calculate location and scale parameters for candidate set of models
getGrad

Calculate the gradient for the non-linear part of a DRMod object
sampSize

Sample size calculations for MCPMod