print.emaxsimB {clinDR}R Documentation

Print simulation output from emaxsimB

Description

Prints key summary variables of Emax estimation peformance for each simulation. Can be used to identify simulated data sets yielding unusual estimates.

Usage

## S3 method for class 'emaxsimB'
print(x, 
      nprint = min(nsim, 20), 
      id = x$idmax, 
      digits = 3, ...)

Arguments

x

Output of emaxsimB

nprint

Number of simulations to print. If a vector of length 2, nprint is the range of simulations to print.

id

Output includes the stdBias for the dose with index id vs placebo

digits

Number of decimal digits to print for Z and p-values

...

Other print parameters (none currently implemented)

Value

Printed output returned as invisible matrix.

Note

The stdBias printed is the difference between the posterior mean of the dose response at the dose with index id and its population value. The difference is divided by the SE (posterior SD).

Author(s)

Neal Thomas

See Also

emaxsimB, summary.emaxsimB, plot.emaxsimB

Examples


## Not run: 
## emaxsimB changes the random number seed
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)
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)

print(D1)

## End(Not run)

[Package clinDR version 2.3.5 Index]