ED: Estimating effective dosage

Description

'ED' estimates effective dosage values (EDx) using a single model fit.

Usage

ED(obj, percVec, od = FALSE, ...)

Arguments

obj

an object of class 'drc'.

percVec

a numeric vector containing the dosage values.

logical. If TRUE adjustment for over-dispersion is used.

...

additional arguments for the function doing the calculations.

Value

A matrix with two columns: one containing the estimates and one containing the corresponding estimated standard errors.

Details

This function is only implemented for the built-in functions of class 'braincousens', 'gompertz', 'logistic' and 'mlogistic'. For objects of class 'braincousens' or 'mlogistic' the additional argument may be the 'upper' argument or the 'interval' argument. The 'upper' argument specifies the upper limit of the bisection method. The upper limit needs to be larger than the EDx level to be calculated. The default limit is 1000, but this may need to be increased. The 'interval' argument should specify a rough interval in which the dose yielding the maximum hormetical response lies. The default interval is 'c(0.001, 1000)'. Notice that the lower limit should not be set to 0 (use something like 1e-3, 1e-6, ...).

Examples

Run this code

model1<-multdrc(FA)

ED(model1, c(10,50,90))[,1]   
## first column: the estimates of ED10, ED50 and ED90
## second column: the estimated standard errors 

rm(model1)