predict.fitEmax {clinDR}  R Documentation 
The estimated means from an Emax model is computed along with confidence bounds. The results are computed for a vector of input dose levels. For binary outcomes, the results are computed on the logit scale and then backtransformed.
## S3 method for class 'fitEmax'
predict(object,dosevec,clev=0.9,
int=1,dref=0, xvec=NULL, ...)
object 
Output of 
dosevec 
Vector of doses to be evaluated. 
clev 
Confidence level for intervals about the estimated mean/proportion at each dosevec. 
int 
The index for the protocol (intercept) to use for the predictions 
dref 
Differences in response between 
xvec 
The vector of centered baseline values for the prediction model when

... 
No additonal parameters will be utilized. 
Model estimates, standard errors, and confidence bounds are computed with the
function SeEmax
.
If baseline covariates were included in the fit and xvec
is not specified,
then the predicted value is the mean of the predictions for all patients in the
specified protocol. Note that the protocol must be specified, or the
prediction defaults to patients from the first protocol. Note that for binary
data, the distinction between the mean of the predicted values and the predicted
value as the mean of the covariates can be important.
A list with estimated dose group means/proportions, lower bound, upper bound, SE, and corresponding values for differences with the reference dose. One value for each dose in dosevec.
Neal Thomas
## Not run:
## this example changes the random number seed
doselev<c(0,5,25,50,100,350)
n<c(78,81,81,81,77,80)
### population parameters for simulation
e0<2.465375
ed50<67.481113
dtarget<100
diftarget<9.032497
emax<solveEmax(diftarget,dtarget,log(ed50),1,e0)
sdy<8.0
pop.parm<c(log(ed50),emax,e0)
dose<rep(doselev,n)
meanlev<emaxfun(dose,pop.parm)
y<rnorm(sum(n),meanlev,sdy)
testout<fitEmax(y,dose,modType=4)
predout<predict(testout,dosevec=c(20,80),int=1)
## End(Not run)