"Extract.emaxsimB" {clinDR} R Documentation

## Extract a simulation from the output of emaxsimB

### Description

Extract a simulated data set from the output of emaxsimB. Data are re-created using the stored random number seed.

### Usage

## S3 method for class 'emaxsimB'
x[i, ...]


### Arguments

 x Output object from emaxsimB i Simulation replication to extract ... Parameters passed to other functions (none currently)

### Details

Re-creates the ith simulated data set for subsequent analyses. Also returns all analyses done for the ith data set in emaxsimB

### Value

A list is returned with class(emaxsimBobj) containing:

 y Response vector dose Doses corresponding to y pop Population parameters; type of parameter depends on constructor function generating study data. popSD Vector containing the population SD used to generate continuous data. NULL for binary data. binary When TRUE, binary data modeled on the logit scale modType modType=3, 4, for the hyperbolic and sigmoidal Emax models. predpop Population means for each dose group dm Vector containing dose group means dsd Vector containing dose group SDs fitpred Posterior means of the dose groups means sepred SE (posterior SD) corresponding to the estmates in fitpred sedif SE (posterior SD) for the differences with placebo bfit Bayesian fitted model of class fitEmaxB. prior, mcmc See fitEmax for documentation. pVal, selContrast P-value and contrast selected from MCP-MOD test idmax Index of default dose group for comparison to placebo

### Note

Extraction from a simulation object requires re-creation of the simulated data set. If the extracted object is to be used more than once, it is more efficient to save the extracted object than reuse [].

### Author(s)

Neal Thomas

emaxsimB, print.emaxsimBobj, plot.emaxsimBobj

### Examples


## Not run:

save.seed<-.Random.seed
set.seed(12357)

nsim<-50
idmax<-5
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)