RandEmax {clinDR} | R Documentation |
Creates a list object that contains inputs and a function to create simulated data sets for emaxsim. Data sets are created by generating random parameters from beta or log-normal distributions for a 3/4 parameter Emax model. For binary data, the Emax model is on the logit scale and then back-transformed.
RandEmax(n, doselev,
parmEmax,
parmE0,
p50,
parmED50=c(3,0.79,0.6),
parmLambda=c(3.03,18.15,0,6),
resSD,
dfSD=Inf,
binary=FALSE)
n |
Sample size for each dose group. |
doselev |
Dose levels (including 0 for placebo) included in the
study corresponding to |
parmEmax |
Vector with mean and standard deviation for a random normal Emax |
parmE0 |
Vector with mean and standard deviation for a random normal intercept. |
p50 |
The predicted ED50 |
parmED50 |
The log(ED50) is generated from a t-distribution
with |
parmLambda |
For a beta distributed sigmoid lambda, a vector with (df1,df2,lower bound, upper bound). For a hyperbolic model, lambda=1. |
resSD |
Standard deviation for residuals within each dose (normal data only) |
dfSD |
If a finite value is specified, the within-dose group SD is randomly generated from resSD times sqrt(dfSD/chisquare(dfSD))), which is the form of a posterior distribution for a SD based on a existing sample. |
binary |
When |
All parameters are independent. 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
Thomas, N., Sweeney, K., and Somayaji, V. (2014). Meta-analysis of clinical dose response in a large drug development portfolio. <doi:10.1080/19466315.2014.924876>
A list of length 2
.
The first element is itself a list named genP
that contains named elments
n
, resSD
, dfSD
, doselev
, dose
,
binary
and the
elements parmE0
, p50
, parmED50
, parmEmax
,
and parmLambda
.
which are specific to RandEmax
. The second
element is a function named genFun
that takes
genP
as input and returns a list with named elements meanlev
,
parm
, resSD
, y
.
Neal Thomas
simParm<-RandEmax(n=c(99,95,98,94,98,98),doselev=c(0,5,10,25,50,150),
parmE0=c(-2.6,2.5),p50=25,parmEmax=c(-1.25,2),resSD=3.88)