predict.emaxsimBobj {clinDR}

Mean response estimates (posterior means) and SE (posterior SD) for specified doses for a simulated emaxsimBobj object

Description

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.

Usage

## S3 method for class 'emaxsimBobj'
predict(object, 
                dose, dref=0, clev=0.9, 
                ...)

Arguments

object

Output of the extract function [] applied to an object createad by emaxsimB.

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.

Value

A list containing:

pred

Vector with mean dose response estimates for each specified dose.

fitdif

Corresponding differences with placebo.

se

SEs (posterior SD) for pred.

sedif

SEs (posterior SD) for fitdif.

lb, ub, lbdif, ubdif

Bounds of clev posterior intervals.

Author(s)

Neal Thomas

See Also

emaxsim, summary.emaxsim, predict.emaxsim

Examples

## 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)