# Compute the MLE (and its SE) of the dose achieving a specified target improvement from placebo. The MLE (se) of the dose required to achieve a targetted improvement from placebo. The fit can be from a 3- or 4- parameter Emax model or output from function emaxalt, or an object of class emaxsimobj. The Emax model is on the logit scale for binary data. ```r targetD (fit, target, modType=4, binary=FALSE) ``` ## Arguments - `fit`: Output of `nls` `fit` to a 3- or 4-parameter Emax model. The order of the parameters in the fit must be (log(ed50),emax,e0) or (log(ed50),lambda,emax,e0). `fit` can also be a list with the first element the coefficient vector, and the second element the variance-covariance matrix. Alternatively, `fit` may be of class `emaxalt` or `emaxsimobj`, and the target dose is based on the fitted model. - `target`: Targetted change from placebo (positive or negative). - `modType`: Value is 3 or 4 for the 3 or 4-parameter Emax model output from nls with parameters in the order (ed50,emax,e0) or (ed50,lambda,emax,e0). `modType` is ignored if fit is from `emaxalt` or `emaxsimobj`. - `binary`: When `TRUE`, the fit is assumed to be for binary data on the logistic scale. `target` is input as a risk difference, and transformed internally. When the `fit` is of class `emaxalt` or `emaxsimobj`, the `binary` status is taken from the object and `binary` is ignored. ## Returns Returns a vector with two elements: - **targetDose**: The MLE of the dose achieving the target. - **seTD**: SE for target.dose ## Note Asymptotic SE computed using the delta method ## Author(s) Neal Thomas ## See Also `SeEmax`, `emaxalt` ## Examples ```r ## Not run: ## emaxsim changes the random number seed doselev<-c(0,5,25,50,100,250) n<-c(78,81,81,81,77,80) dose<-rep(doselev,n) ### 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(led50=log(ed50),emax=emax,e0=e0) meanresp<-emaxfun(dose,pop) y<-rnorm(sum(n),meanresp,sdy) nls.fit<-nls(y ~ e0 + (emax * dose)/(dose + exp(led50)), start = pop, control = nls.control( maxiter = 100),trace=TRUE,na.action=na.omit) targetD(nls.fit,10,modType=3) ### ### apply targetD to an emaxsim object ### nsim<-50 sdy<-25 gen.parm<-FixedMean(n,doselev,emaxfun(doselev,pop),sdy) D4 <- emaxsim(nsim,gen.parm,modType=4) summary(D4,testalph=0.05) out<-NULL for(i in 1:nsim){ out<-rbind(out,targetD(D4[i],target=4)) } ## End(Not run) ```

targetD function