# 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, 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 ```r 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 ## Returns 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 ```r ## 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) ```