fitEmax {clinDR}  R Documentation 
Calls NewtonRaphson optimizers, nls and nlm, for a hyperbolic or sigmoidal Emax model. Different intercepts for multiple protocoldata are supported. For binary data, the Emax model is on the logit scale.
fitEmax(y,dose,iparm,xparm,modType=4,
prot=rep(1,length(y)),count=rep(1,length(y)),xbase=NULL,
binary=FALSE,diagnostics=TRUE,msSat=NULL,
pboAdj=rep(FALSE,max(prot)),optObj=TRUE)
y 
Outcome for each patient. Missing 
dose 
Dose for each patient. 
iparm 
Optional starting values for the NewtonRaphson algorithm. The order of the variables is (log(ED50),Emax,E0) or (log(ED50),lambda,Emax,E0). Note the transformation of ED50. If there is more than one protocol, the E0 is automatically duplicated. 
xparm 
Optional starting values for the baseline covariate slopes (if any).

modType 
modType=3 (default) for the 3parameter hyperbolic Emax model. modType=4 for the 4parameter sigmoidal Emax model. 
prot 
Protocol (group) membership used to create multiple intercepts. The default is a single protocol. 
count 
Counts for the number of patients when the 
xbase 
A matrix of baseline covariates with rows corresponding to

diagnostics 
Print trace information per iteration and any error messages from the optimizing methods. Printing can be suppressed for use in simulation studies. 
binary 
When 
msSat 
If continuous 
pboAdj 
For published data with only pboadjusted dose group means and
SEs, the model is fit without an intercept(s). If initial parameters
are supplied, the intercept (E0) should be assigned 
optObj 
Include the output object from the R optimization code in the 
Fits the 3 or 4 Emax model using
nls
. A newtonraphson algorithm is tried first
followed by a partial linear optimatization if needed. Binary
data are fit using nlm
.
A list assigned class "fitEmax" with:
fit 
The parameter estimates and their variancecovariance matrix. 
y, dose, modType, prot, count, binary, pboAdj 
Input values. 
gofTest 
Goodness of fit pvalue based on likelihood ratio comparison of the model to a saturated fit. 
nll 

df 
Residual degrees of freedom for the Emax model and the saturated model. 
optobj 
When requested, the fit object returned by the R optimation functions. 
Neal Thomas
nls
, nlm
, nllogis
,
predict.fitEmax
, plot.fitEmax
, coef.fitEmax
## the example changes the random number seed
doselev<c(0,5,25,50,100,350)
n<c(78,81,81,81,77,80)
### population parameters for simulation
e0<2.465375
ed50<67.481113
dtarget<100
diftarget<9.032497
emax<solveEmax(diftarget,dtarget,log(ed50),1,e0)
sdy<8.0
pop<c(log(ed50),emax,e0)
dose<rep(doselev,n)
meanlev<emaxfun(dose,pop)
y<rnorm(sum(n),meanlev,sdy)
testout<fitEmax(y,dose,modType=4)