fitGain | R Documentation |
Get the fiited values for the gain values at all dose levels based on a given pseudo DLE model, DLE sample, a pseudo efficacy model, a Efficacy sample and data. This method returns a data frame with dose, middle, lower and upper quantiles of the gain value samples
fitGain(DLEmodel, DLEsamples, Effmodel, Effsamples, data, ...) ## S4 method for signature 'ModelTox,Samples,ModelEff,Samples,DataDual' fitGain( DLEmodel, DLEsamples, Effmodel, Effsamples, data, points = data@doseGrid, quantiles = c(0.025, 0.975), middle = mean, ... )
DLEmodel |
the DLE pseudo model of |
DLEsamples |
the DLE samples of |
Effmodel |
the efficacy pseudo model of |
Effsamples |
the efficacy samples of |
data |
the data input of |
... |
additional arguments for methods |
points |
at which dose levels is the fit requested? default is the dose grid |
quantiles |
the quantiles to be calculated (default: 0.025 and 0.975) |
middle |
the function for computing the middle point. Default:
|
fitGain(
DLEmodel = ModelTox,
DLEsamples = Samples,
Effmodel = ModelEff,
Effsamples = Samples,
data = DataDual
)
: This method returns a data frame with dose, middle, lower, upper quantiles for
the gain values obtained given the DLE and the efficacy samples
##Obtain the 'fitGain' the middle, uppper and lower quantiles for the samples of gain values ## at all dose levels using a pseudo DLE model, a DLE sample, a pseudo Efficacy model and ## a efficacy sample ## data must be from 'DataDual' class 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) ## DLE model must be from 'ModelTox' class e.g using 'LogisticIndepBeta' model DLEmodel<-LogisticIndepBeta(binDLE=c(1.05,1.8),DLEweights=c(3,3),DLEdose=c(25,300),data=data) ## Efficacy model must be from 'ModelEff' class e.g using 'Effloglog' model Effmodel<-Effloglog(c(1.223,2.513),c(25,300),nu=c(a=1,b=0.025),data=data,c=0) ## samples must be from 'Samples' class (object slot in fit) options<-McmcOptions(burnin=100,step=2,samples=200) ##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) DLEsamples <- mcmc(data=data1,model=DLEmodel,options=options) Effsamples <- mcmc(data=data,model=Effmodel,options=options) fitGain(DLEmodel=DLEmodel,DLEsamples=DLEsamples, Effmodel=Effmodel, Effsamples=Effsamples,data=data)
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