plotDualResponses: Plot of the DLE and efficacy curve side by side given a DLE...

Description Usage Arguments Value Methods (by class) Examples

Description

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

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
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)

Value

This returns the ggplot object with the dose-toxicity and dose-efficacy model fits

Methods (by class)

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
## 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)

crmPack documentation built on June 13, 2019, 9:02 a.m.