randomEmax {clinDR} | R Documentation |
Random data constructor function for emaxsim(B) creating random parameters for an Emax model for continuous or binary data.
Description
Creates a list object that contains inputs and a function to create
simulated data sets for emaxsim(B). Data sets are created by
generating random parameters from an emaxPrior.control()
object for
a 3/4 parameter Emax model. For binary data, the Emax model is
on the logit scale and then back-transformed.
Usage
randomEmax(x,n,doselev,modType=c('4','3'))
Arguments
x |
Object of type |
n |
Sample size for each dose group. |
doselev |
Dose levels (including 0 for placebo) included in the
study corresponding to |
modType |
Specifies a 4-parameter sigmoidal Emax model, or a 3-parameter hyperbolic Emax model |
Details
Normal data are generated from the dose response curves with homogeneous-variance normal residuals. Binary data are 0/1 generated from Bernoulli distributions with proportions computed by transforming the Emax model output from the logit to proportion scale. Default values are based on recommendations in the references.
Value
A list of length 2
.
The first element is itself a list named genP
that contains named elments
n
, doselev
, dose
,
modType
and the emaxPrior
object x
.
The second element is a function named genFun
that takes
genP
as input and returns a list with named elements meanlev
,
parm
, resSD
, y
.
Author(s)
Neal Thomas
References
Thomas, N., Sweeney, K., and Somayaji, V. (2014). Meta-analysis of clinical dose response in a large drug development portfolio, Statistics in Biopharmaceutical Research, Vol. 6, No.4, 302-317. <doi:10.1080/19466315.2014.924876>
Thomas, N., and Roy, D. (2016). Analysis of clinical dose-response in small-molecule drug development: 2009-2014. Statistics in Biopharmaceutical Research, Vol. 6, No.4, 302-317 <doi:10.1080/19466315.2016.1256229>
Wu, J., Banerjee, A., Jin, B. Menon, M. S., Martin, S. and Heatherington, A. (2017). Clinical dose response for a broad set of biological products: A model-based meta-analysis. Statistical Methods in Medical Research. <doi:10.1177/0962280216684528>
See Also
Examples
prior<-emaxPrior.control(epmu=0,epsca=4,
difTargetmu=0,difTargetsca=4,dTarget=20,
p50=(2+5)/2,
sigmalow=0.01,sigmaup=3)
simParm<-randomEmax(x=prior,n=c(99,95,98,94,98,98),
doselev=c(0,5,10,25,50,150),modType="4")
# D1 <- emaxsimB(nsim=10,simParm,prior,nproc=1)