emaxalt {clinDR} R Documentation

## Fit 4- or 3-parameter Emax model substituting simpler curves if convergence not achieved.

### Description

ML estimation for 4- and 3-parmeter Emax model. If the 4-parameter model is requested, it is estimated and the 3-parameter model is fit only if the 4-parameter estimation fails. If 3-parameter estimation fails, the linear, log-linear, or exponential model producing the smallest residual SS is substituted. For binary data, the model is fit on the logit scale and then back-transformed.

### Usage

emaxalt(y, dose, modType=3,binary=FALSE,
iparm=NA,ed50cutoff=2.5*max(doselev),
ed50lowcutoff=doselev[2]/1000,switchMod= TRUE,
truncLambda=6)


### Arguments

 y Response vector dose Doses corresponding to y modType When modType=4, the fitting begins with the 4 parameter model. If estimation fails or modType=3, the 3-parameter estimation is applied. If it fails, a best-fitting model linear in its parameters is selected. binary When specified, the Emax model is fit on the logit scale, and then the results are back-transformed to proportions. iparm Vector of optional initial values for the Emax fit. Starting values are computed if not specified. ed50cutoff Upper allowed limit for ED50 estimates. ed50lowcutoff Lower allowed limit for the ED50 estimates. switchMod If switchMod is TRUE, the algorithm substitutes a simpler model if (1) convergence is not achieved, (2) the information matrix is not positive definite at the converged values, (3) the ED50 estimates are outside the cutoff bounds. If switchMod is F, only conditions (1) or (2) cause a simpler model to be used. truncLambda When modType=4 and the converged estimate of the Hill parameter lambda exceeds truncLambda, the model fit is judged unstable and discarded. Set truncLambda=Inf for no truncation.

### Details

The partial linear method is used in nls. If it fails, gauss-newton is attempted. If both methods fail, the next simpler model is attempted. For the 4-parameter model, the next step is the 3-parameter model. For the 3-parameter model, a linear, log-linear log(dose+1.0), and exp(dose/max(dose)) are fit using lm, and the 2-parm fit with the smallest residual SS is selected.

### Value

A list assigned class "emaxalt" with the following elements:

 dm Vector containing dose group means dsd Vector containing dose group SDs Sparm Vector of starting values for 3-parameter Emax fit. fitType Character vector with "4", "3", "L", "LL", or "E" for 4-Emax, 3-Emax, linear, log-linear, or exponential when an alternative model is selected. vc The variance-covariance matrix of the model parameters stored as a vector. The length is 16, 9, 4 depending on fitType. fitpred Dose groups means estimated from the model residSD The residual SD based on the selected model. sepred SEs for estimates in fitpred sedif SEs for model-based estimates of difference with placebo bigC bigC= TRUE if the primary fit (from modType) yielded an ED50 >ED50 upper limit. negC negC= TRUE if the primary fit (from modType) yielded a ED50 estimate < ED50 lower limit. est4 4-parmameter Emax fit (ed50,lambda,emax,e0). NA if failed to converge or 3-parameter model requested. est3 3-parmameter Emax fit (ed50,emax,e0). NA if failed to converge or 4-parameter model successfully fit. estA Alternative parameter estimates. NA if Emax model fit successfully

### Author(s)

Neal Thomas

emaxsim, nls

### Examples


save.seed<-.Random.seed
set.seed(12357)

doselev<-c(0,5,25,50,100)
n<-c(78,81,81,81,77)
dose<-rep(doselev,n)

### 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)
meanresp<-emaxfun(dose,pop)
y<-rnorm(sum(n),meanresp,sdy)

simout<-emaxalt(y,dose)

simout2<-emaxalt(y,dose,modType=4)

.Random.seed<-save.seed


[Package clinDR version 2.3.5 Index]