Predict Doses for Binomial Assay model
Calibrate binomial assays, generalizing the calculation of LD50.
dose.p(obj, cf = 1:2, p = 0.5)
obj |
A fitted model object of class inheriting from |
cf |
The terms in the coefficient vector giving the intercept and coefficient of (log-)dose |
p |
Probabilities at which to predict the dose needed. |
An object of class "glm.dose" giving the prediction (attribute
"p" and standard error (attribute "SE") at each response
probability.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Springer.
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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.