ExpEff {crmPack}

Compute the expected efficacy based on a given dose, a given pseudo Efficacy log-log model and a given efficacy sample

Description

Compute the expected efficacy based on a given dose, a given pseudo Efficacy log-log model and a given efficacy sample

Usage

ExpEff(dose, model, samples, ...)

## S4 method for signature 'numeric,Effloglog,Samples'
ExpEff(dose, model, samples, ...)

## S4 method for signature 'numeric,Effloglog,missing'
ExpEff(dose, model, samples, ...)

## S4 method for signature 'numeric,EffFlexi,Samples'
ExpEff(dose, model, samples, ...)

Arguments

dose

the dose

model

the Effloglog class object

samples

the Samples class object (can also be missing)

...

unused

Functions

• ExpEff(dose = numeric, model = Effloglog, samples = Samples): Method for the Effloglog class

• ExpEff(dose = numeric, model = Effloglog, samples = missing): Compute the Expected Efficacy based a given dose and a given Pseudo Efficacy log log model without samples

• ExpEff(dose = numeric, model = EffFlexi, samples = Samples): Compute the Expected Efficacy based a given dose, Efficacy Flexible model with samples

Examples

##Obtain the expected efficacy value for a given dose, a given pseudo 
## efficacy model and a given efficacy sample
##The efficacy model must be from 'ModelEff' class (model slot)
##The efficacy sample must be from 'Samples' class (sample slot)
emptydata<-DataDual(doseGrid=seq(25,300,25))
data<-emptydata
model<- EffFlexi(Eff=c(1.223, 2.513),Effdose=c(25,300),
                 sigma2=c(a=0.1,b=0.1),sigma2betaW=c(a=20,b=50),smooth="RW2",data=data)
options<-McmcOptions(burnin=100,step=2,samples=200)
set.seed(94)
samples<-mcmc(data=data,model=model,options=options)
## Given the dose 75 (dose slot)
ExpEff(dose=75,model=model,samples=samples)
##Obtain the expected efficacy value for a given dose and a given pseudo efficacy model 

##The efficacy model must be from 'ModelEff' class (model slot)
emptydata<-DataDual(doseGrid=seq(25,300,25),placebo=FALSE)
data<-emptydata

model<-Effloglog(Eff=c(1.223,2.513),Effdose=c(25,300),nu=c(a=1,b=0.025),data=data,c=0)


## Given the dose 75 (dose slot)
ExpEff(dose=75,model=model)
##Obtain the expected efficacy value for a given dose, the 'EffFlexi' efficacy model and 
##samples generated from this efficacy model
##The efficacy model must be from 'EffFlexi' class (model slot)
##The efficacy samples must be from 'Samples' class (samples slot)
model<- EffFlexi(Eff=c(1.223, 2.513),Effdose=c(25,300),
                 sigma2=c(a=0.1,b=0.1),sigma2betaW=c(a=20,b=50),smooth="RW2",data=data)
set.seed(94)
samples<-mcmc(data=data,model=model,options=options)
## Given the dose 75 (dose slot)
ExpEff(dose=75,model=model,samples=samples)