clinDR: FixedMean – R documentation

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FixedMean

Fixed means (proportions) random data constructor for emaxsim for continuous or binary data

Description

Creates a list object that contains inputs and a function to create simulated data sets with a common mean (proportion) for use in emaxsim with normal or continuous data

Usage

FixedMean(n, doselev, meanlev, resSD, parm = NULL, binary=FALSE)

Arguments

`n`	Sample size for each dose group
`doselev`	Dose levels (including 0 for placebo) in the study corresponding to `n`. Must be in increasing order.
`meanlev`	Mean response at each doselev. For binary data, these are the proportion of responders (no logit transformation).
`resSD`	Standard deviation for residuals within each dose group (assumed common to all dose groups)
`parm`	Population parameters that are saved for later reference, but are not used when creating simulated data. `parm` can contain parameters for a 3- or 4- parameter Emax model that generated `meanlev`. They should be stored in the order given in `emaxfun`. Default is `NULL`.
`binary`	Normal data with homogeneous variance are generated unless `binary` is `TRUE`, and then means are interpreted as proportions and `0/1` data are generated.

Value

A list of length 2. The first element is itself a list named genP that contains named elments n, resSD, doselev, dose, parm, binary, and the element meanlev, which is specific to FixedMean. 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

Examples

## Not run: 
##  example changes the random number seed

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<-c(log(ed50),emax,e0)  
  
meanlev<-emaxfun(doselev,pop)  

###FixedMean is specialized constructor function for emaxsim
genp<-FixedMean(n,doselev,meanlev,sdy,pop)  

### binary example
n<-rep(500,5)
doselev<-c(0,5,25,50,1000)
dose<-rep(doselev,n)

e0<- qlogis(0.2)
ed50<-20
diftarget<-qlogis(0.6)-qlogis(0.2)
lambda<-2
dtarget<-100
emax<-solveEmax(diftarget,dtarget,log(ed50),lambda,e0)

pop<-c(log(ed50),lambda,emax,e0)
meanlev<-plogis(emaxfun(doselev,pop))

genp<-FixedMean(n,doselev,meanlev,sdy,pop,binary=TRUE)  

tapply(genp$genFun(genp$genP)$y,dose,mean)
meanlev


## End(Not run)

clinDR

Simulation and Analysis Tools for Clinical Dose Response Modeling

v2.3.5

GPL (>= 2)

Authors

Neal Thomas [aut, cre] (<https://orcid.org/0000-0002-1915-8487>), Jing Wu [aut], Mike K. Smith [aut]

Initial release

2021-04-11