SeEmax {clinDR} R Documentation

## Asymptotic SE for dose response estimates from a 3- or 4- parameter Emax model

### Description

Compute the asymptotic SE for dose response estimates based on the asymptotic variance-covariance matrix from the fit of a 3- or 4-parameter Emax model

### Usage

SeEmax(fit, doselev, modType, dref=0, nbase=0, x=NULL,
binary=FALSE, clev=0.9)


### Arguments

 fit Output of nls fit to a 3- or 4-parameter Emax model. The order of the parameters in the fit must be (log(ed50),emax,e0) or (log(ed50),lambda,emax,e0). Alternatively, fit can be a list with the first element the coefficient vector, and the second element the variance-covariance matrix. List input can be used with multiple protocols and baseline covariates (see details). doselev SEs are evaluated at vector of doses modType modType=3,4 for a 3 or 4 parameter model. dref A reference dose (0 by default) for contrasts, but other values can be specified. If specified, a single reference value must be given. nbase The number of baseline predictors included in the model. x The model is evaluated at baseline covariate values, x. If x is a matrix, then each row is a vector of baseline predictors, and the results are for the dose response averaged over all of the predictors in x. binary Emax model on logistic scale, then backtransformed. clev Confidence level for intervals.

### Details

The Emax models supported by SeEmax should now be fit using fitEmax and predict.fitEmax. SeEmax remains available primarily for backward compatibility.

SeEmax can be used with models that allow different placebo response for multiple protocols by selecting the intercept for a specific protocol. Coeficients for baseline covariates can also be included following the intercept. The variance-covariance matrix from the full model must be subsetted to match the included coeficients (i.e., the rows and columns corresponding to the omitted intercepts must be removed). List input must be used for the more general models.

### Value

Returns a list:

 doselev Doses to evaluate dref Differences in response between doselev and dref are computed. fitpred  Estimated dose response at doselev sepred SE for estimated dose responses fitdif Estimated response at doselev minus estimated response at placebo sedif SE for fitdif estimated differences fitref Estimated dose response at the reference dose. seref SE for the estimated dose response at the reference dose covref The covariance between each estimated response and the estimated response at the reference dose. These covariances can be used to compute asymptotic variances of differences after back-transformation (e.g., for logistic regression with binary data).

Neal Thomas

### References

Bates, D. M. and Watts, D. G. (1988) Nonlinear Regression Analysis and Its Applications, Wiley

fitEmax

### Examples


## Not run:

## this example changes the random number seed
doselev<-c(0,5,25,50,100,250)
n<-c(78,81,81,81,77,80)
dose<-rep(doselev,n)

### population parameters for simulation
e0<-2.465375
ed50<-67.481113
led50<-log(ed50)
lambda=1.8

dtarget<-100
diftarget<-9.032497
emax<-solveEmax(diftarget,dtarget,log(ed50),lambda,e0)

sdy<-7.967897
pop<-c(led50=led50,lambda=lambda,emax=emax,e0=e0)
meanresp<-emaxfun(dose,pop)
y<-rnorm(sum(n),meanresp,sdy)
nls.fit<-nls(y ~ e0 + (emax * dose^lambda)/(dose^lambda + exp(led50*lambda)),
start = pop, control = nls.control(
maxiter = 100),trace=TRUE,na.action=na.omit)

SeEmax(nls.fit,doselev=c(60,120),modType=4)
SeEmax(list(coef(nls.fit),vcov(nls.fit)),c(60,120),modType=4)

## End(Not run)



[Package clinDR version 2.3.5 Index]