# Compute the dose with confidence interval exceeding a target change from placebo for each simulated example in an emaxsim object. Selects the lowest dose from a user-specified grid of doses with confidence interval exceeding a targetted change from placebo for each simulated data set in an emaxsim object. ```r targetCI (object, target, dgrid, clev=0.90, high= TRUE) ``` ## Arguments - `object`: An emaxsim object - `target`: Target improvement from placebo - `dgrid`: The lowest dose is found by a search over a user-specified grid of doses. If dgrid is a single value, it is interpreted as the number of equally-spaced doses to select from zero to the highest dose in the simulated design. - `clev`: One-sided confidence interval level. - `high`: When TRUE, lower bounds are computed and must be higher than the target. When FALSE, upper bounds must be less than the target. ## Returns Returns a vector with the lowest dose meeting the criteria. If a simulated example does not have a qualifying dose, Inf is returned. ## Note If the grid is very large (>200), execution will slow as a large number of estimates and SEs are computed. ## Author(s) Neal Thomas ## See Also `emaxsim, predict.emaxsim`, targetD ## Examples ```r ## Not run: # emaxsim changes the random number seed nsim<-100 doselev<-c(0,5,25,50,100) n<-c(78,81,81,81,77) ### population parameters for simulation e0<-2.465375 ed50<-67.481113 dtarget<-100 diftarget<-9.032497 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.parm<-FixedMean(n,doselev,meanlev,sdy) D1 <- emaxsim(nsim,gen.parm,modType=3) target<-6 tD<- ( (target*ed50)/(emax-target) ) selectedDose<-targetCI(D1,target,dgrid=c(1:100)+0.5,clev=0.80,high=TRUE) ## End(Not run) ```

targetCI function