plotGain: Plot the gain curve in addition with the dose-DLE and...

In crmPack: Object-Oriented Implementation of CRM Designs

Plot the gain curve in addition with the dose-DLE and dose-efficacy curve using a given DLE pseudo model, a DLE sample, a given efficacy pseudo model and an efficacy sample

Description

Plot the gain curve in addition with the dose-DLE and dose-efficacy curve using a given DLE pseudo model, a DLE sample, a given efficacy pseudo model and an efficacy sample

Plot the gain curve in addition with the dose-DLE and dose-efficacy curve using a given DLE pseudo model, and a given efficacy pseudo model

Usage

plotGain(DLEmodel, DLEsamples, Effmodel, Effsamples, data, ...)

## S4 method for signature 'ModelTox,Samples,ModelEff,Samples'
plotGain(DLEmodel, DLEsamples, Effmodel, Effsamples, data, ...)

## S4 method for signature 'ModelTox,missing,ModelEff,missing'
plotGain(DLEmodel, DLEsamples, Effmodel, Effsamples, data, ...)

Arguments

DLEmodel	the dose-DLE model of ModelTox class object
DLEsamples	the DLE sample of Samples class object
Effmodel	the dose-efficacy model of ModelEff class object
Effsamples	the efficacy sample of of Samples class object
data	the data input of DataDual class object
...	not used

Value

This returns the ggplot object for the plot

Functions

• plotGain( DLEmodel = ModelTox, DLEsamples = Samples, Effmodel = ModelEff, Effsamples = Samples ): Standard method

• plotGain( DLEmodel = ModelTox, DLEsamples = missing, Effmodel = ModelEff, Effsamples = missing ): Standard method

Examples

## we need a data object with doses >= 1:
data <-DataDual(x=c(25,50,25,50,75,300,250,150),
                y=c(0,0,0,0,0,1,1,0),
                w=c(0.31,0.42,0.59,0.45,0.6,0.7,0.6,0.52),
                doseGrid=seq(25,300,25),
                placebo=FALSE)
##plot the dose-DLE , dose-efficacy and gain curve in the same plot with DLE and efficacy samples
##define the DLE model which must be of 'ModelTox' class 
##(e.g 'LogisticIndepBeta' class model)
DLEmodel<-LogisticIndepBeta(binDLE=c(1.05,1.8),DLEweights=c(3,3),DLEdose=c(25,300),data=data)
## define the efficacy model which must be of 'ModelEff' class
## (e.g 'Effloglog' class)
Effmodel<-Effloglog(Eff=c(1.223,2.513),Effdose=c(25,300),nu=c(a=1,b=0.025),data=data,c=0)
##define the DLE sample of 'Samples' class
##set up the same data set in class 'Data' for MCMC sampling for DLE
data1 <- Data(x=data@x,y=data@y,doseGrid=data@doseGrid)

##Define the options for MCMC
options <- McmcOptions(burnin=100,step=2,samples=1000)


DLEsamples <- mcmc(data=data1,model=DLEmodel,options=options)
##define the efficacy sample of 'Samples' class
Effsamples <- mcmc(data=data,model=Effmodel,options=options)
##plot the three curves of mean values of the DLEsamples, Effsamples and 
##gain value samples (obtained within this plotGain function) at all dose levels
plotGain(DLEmodel=DLEmodel,DLEsamples=DLEsamples,
         Effmodel=Effmodel,Effsamples=Effsamples,
         data=data)
## we need a data object with doses >= 1:
data <-DataDual(x=c(25,50,25,50,75,300,250,150),
                y=c(0,0,0,0,0,1,1,0),
                w=c(0.31,0.42,0.59,0.45,0.6,0.7,0.6,0.52),
                doseGrid=seq(25,300,25),
                placebo=FALSE)
##plot the dose-DLE , dose-efficacy and gain curve in the same plot with DLE and efficacy samples
##define the DLE model which must be of 'ModelTox' class 
##(e.g 'LogisticIndepBeta' class model)
DLEmodel<-LogisticIndepBeta(binDLE=c(1.05,1.8),DLEweights=c(3,3),DLEdose=c(25,300),data=data)
## define the efficacy model which must be of 'ModelEff' class
## (e.g 'Effloglog' class)
Effmodel<-Effloglog(Eff=c(1.223,2.513),Effdose=c(25,300),nu=c(a=1,b=0.025),data=data,c=0)
##plot the three curves of using modal estimates of model parameters at all dose levels
plotGain(DLEmodel=DLEmodel,
         Effmodel=Effmodel,
         data=data)

crmPack documentation built on Sept. 3, 2022, 1:05 a.m.