predict.emaxsimBobj | R Documentation |
Estimated mean and standard error for specified doses (posterior means and SD) computed from the output of a simulated data set created by function emaxsimB. Also returns mean difference with placebo and their standard errors.
## S3 method for class 'emaxsimBobj'
predict(object,
dose, dref=0, clev=0.9,
...)
object |
Output of the extract function [] applied to an object
createad by |
dose |
Vector (can be a single value) of doses where dose response curve is to be evaluated. |
dref |
A reference dose (0 by default) for contrasts, but other values can be specified. If specified, a single reference value must be given. |
clev |
Specified probablity of the posterior interval |
... |
Optional arguments are not used. |
A list containing:
pred |
Vector with mean dose response estimates for each specified dose. |
fitdif |
Corresponding differences with placebo. |
se |
SEs (posterior SD) for |
sedif |
SEs (posterior SD) for |
lb, ub, lbdif, ubdif |
Bounds of |
Neal Thomas
emaxsim
, summary.emaxsim
,
predict.emaxsim
## Not run:
### emaxsimB changes the random number seed
nsim<-50
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)
predict(D1[1],dose=c(75,125))
## End(Not run)
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