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

ExpEff function