predict.emaxsim {clinDR}

Mean response and SE for specified doses for each replicate data set in an emaxsim object

Description

Estimated mean/proportion and standard error for each simulated data set in an emaxsim object. Also returns mean difference with placebo and their standard errors.

Usage

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

Arguments

object

Output of emaxsim

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.

...

Optional arguments are not used.

Value

A list containing:

fitpredv

Matrix with mean dose response estimate for each simulated data set. Number of columns is the number of doses specified.

fitdifv

Matrix with mean dose response estimate minus mean placebo response for each simulated data set. Number of columns is the number of doses specified.

sepredv

Matrix of SEs for fitpredv.

sedifv

Matrix of SEs for fitdifv.

Author(s)

Neal Thomas

See Also

emaxsim, summary.emaxsim, plot.emaxsim

Examples

## Not run: 
## random number seed changed by this example
nsim<-50
idmax<-5
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.parm<-c(log(ed50),emax,e0)    
meanlev<-emaxfun(doselev,pop.parm)  

###FixedMean is specialized constructor function for emaxsim
gen.parm<-FixedMean(n,doselev,meanlev,sdy)  
D1 <- emaxsim(nsim,gen.parm)

predout<-predict(D1,c(75,150))

## End(Not run)