crmPack (version 1.0.6)

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

Value

This returns the ggplot

object for the plot

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

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)