Predict Doses for Binomial Assay model

DESCRIPTION:

Calibrate binomial assays, generalizing the calculation of LD50.

USAGE:

dose.p(obj, cf = 1:2, p = 0.5)

REQUIRED ARGUMENTS:

obj
A fitted model object of class inheriting from "glm".

OPTIONAL ARGUMENTS:

cf
The terms in the coefficient vector giving the intercept and coefficient of (log-)dose
p
Probabilities at which to predict the dose needed.

VALUE:

An object of class "glm.dose" giving the prediction and standard error at each response probability.

REFERENCES:

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Springer.

EXAMPLES:

ldose <- rep(0:5, 2)
numdead <- c(1, 4, 9, 13, 18, 20, 0, 2, 6, 10, 12, 16)
sex <- factor(rep(c("M", "F"), c(6, 6)))
SF <- cbind(numdead, numalive = 20 - numdead)
budworm.lg0 <- glm(SF ~ sex + ldose - 1, family = binomial)
dose.p(budworm.lg0, cf = c(1,3), p = 1:3/4)
dose.p(update(budworm.lg0, family = binomial(link=probit)),
       cf = c(1,3), p = 1:3/4)