# Plot dose response from a data set generated by emaxsimB Plot of population dose response curve, sample dose group means, posterior and posterior predictive intervals, and the model-based estimated (posterior means) dose response curve. ```r ## S3 method for class 'emaxsimBobj' plot( x, clev=0.9, plotDif=FALSE, plotPop=c('m','3','4'), logScale=FALSE, plotResid=FALSE, plot=TRUE, ... ) ``` ## Arguments - `x`: Extracted data object from `emaxsimB` - `clev`: Level for posterior intervals - `plotDif`: When `TRUE`, the difference with placebo is plotted. - `plotPop`: When plotPop='m', the mean values at each dose in the designs are joined using linear interpolation. Otherwise, the the population Emax parameters must be supplied with the data generator (see FixedMean or RandEmax ). If the Emax parameters are not available, linear interpolation is used. - `logScale`: Not implemented - `plotResid`: Not implemented - `plot`: Return plotting output without plotting. - ``...``: Other plot parameters. See `plot.fitEmaxB` for details ## Note The estimated curve is the posterior mean evaluated along a grid of dose values. ## Examples ```r ## Not run: ## emaxsimB changes the random number seed nsim<-50 idmax<-5 doselev<-c(0,5,25,50,100) n<-c(78,81,81,81,77) Ndose<-length(doselev) ### population parameters for simulation e0<-2.465375 ed50<-67.481113 dtarget<-100 diftarget<-2.464592 emax<-solveEmax(diftarget,dtarget,log(ed50),1,e0) sdy<-7.967897 pop<-c(log(ed50),emax,e0) meanlev<-emaxfun(doselev,pop) ###FixedMean is specialized constructor function for emaxsim gen<-FixedMean(n,doselev,meanlev,sdy) nsim<-50 idmax<-5 doselev<-c(0,5,25,50,100) n<-c(78,81,81,81,77) Ndose<-length(doselev) ### population parameters for simulation e0<-2.465375 ed50<-67.481113 dtarget<-100 diftarget<-2.464592 emax<-solveEmax(diftarget,dtarget,log(ed50),1,e0) sdy<-7.967897 pop<-c(log(ed50),emax,e0) meanlev<-emaxfun(doselev,pop) ###FixedMean is specialized constructor function for emaxsim gen<-FixedMean(n,doselev,meanlev,sdy) prior<-emaxPrior.control(epmu=0,epsca=30,difTargetmu=0, difTargetsca=30,dTarget=100,p50=50,sigmalow=0.1, sigmaup=30,parmDF=5) mcmc<-mcmc.control(chains=1,warmup=500,iter=5000,seed=53453,propInit=0.15,adapt_delta = 0.95) D1 <- emaxsimB(nsim,gen, prior, modType=3,mcmc=mcmc,check=FALSE) plot(D1,id=3) mcmc<-mcmc.control(chains=1,warmup=500,iter=5000,seed=53453,propInit=0.15,adapt_delta = 0.95) D1 <- emaxsimB(nsim,gen, prior, modType=3,mcmc=mcmc,check=FALSE) plot(D1[2]) ## End(Not run) ```

plot.emaxsimBobj function