# Plot of the DLE and efficacy curve side by side given a DLE pseudo model, a DLE sample, an efficacy pseudo model and a given efficacy sample Plot of the DLE and efficacy curve side by side given a DLE pseudo model, a DLE sample, an efficacy pseudo model and a given efficacy sample Plot of the dose-DLE and dose-efficacy curve side by side given a DLE pseudo model and a given pseudo efficacy model without DLE and efficacy samples ```r plotDualResponses(DLEmodel, DLEsamples, Effmodel, Effsamples, data, ...) ## S4 method for signature 'ModelTox,Samples,ModelEff,Samples' plotDualResponses( DLEmodel, DLEsamples, Effmodel, Effsamples, data, extrapolate = TRUE, showLegend = FALSE, ... ) ## S4 method for signature 'ModelTox,missing,ModelEff,missing' plotDualResponses(DLEmodel, DLEsamples, Effmodel, Effsamples, data, ...) ``` ## Arguments - `DLEmodel`: the pseudo DLE model of `ModelTox` class object - `DLEsamples`: the DLE samples of `Samples` class object - `Effmodel`: the pseudo efficacy model of `ModelEff` class object - `Effsamples`: the Efficacy samples of `Samples` class object - `data`: the data input of `DataDual` class object - ``...``: additional arguments for the parent method `plot,Samples,Model-method` - `extrapolate`: should the biomarker fit be extrapolated to the whole dose grid? (default) - `showLegend`: should the legend be shown? (not default) ## Returns This returns the `ggplot` object with the dose-toxicity and dose-efficacy model fits ## Functions * `plotDualResponses( DLEmodel = ModelTox, DLEsamples = Samples, Effmodel= ModelEff, Effsamples = Samples )`: function todo * `plotDualResponses( DLEmodel = ModelTox, DLEsamples = missing, Effmodel= ModelEff, Effsamples = missing )`: Plot the DLE and efficacy curve side by side given a DLE model and an efficacy model without any samples ## 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 and dose-efficacy curves in two plots 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) ##Specify 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 dose-DLE and dose-efficacy curves with two plot side by side. ##For each curve the 95% credibility interval of the two samples are alos given plotDualResponses(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 and dose-efficacy curves in two plots without 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 dose-DLE and dose-efficacy curves with two plot side by side. plotDualResponses(DLEmodel=DLEmodel, Effmodel=Effmodel, data=data) ```

plotDualResponses function