plotDualResponses  R Documentation 
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 doseDLE and doseefficacy curve side by side given a DLE pseudo model and a given pseudo efficacy model without DLE and efficacy samples
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, ...)
DLEmodel 
the pseudo DLE model of 
DLEsamples 
the DLE samples of 
Effmodel 
the pseudo efficacy model of 
Effsamples 
the Efficacy samples of 
data 
the data input of 
... 
additional arguments for the parent method

extrapolate 
should the biomarker fit be extrapolated to the whole dose grid? (default) 
showLegend 
should the legend be shown? (not default) 
This returns the ggplot
object with the dosetoxicity and doseefficacy model fits
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
## 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 doseDLE and doseefficacy 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 doseDLE and doseefficacy 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 doseDLE and doseefficacy 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 doseDLE and doseefficacy curves with two plot side by side. plotDualResponses(DLEmodel=DLEmodel, Effmodel=Effmodel, data=data)
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