dose.p: Predict Doses for Binomial Assay model
In MASS: Support Functions and Datasets for Venables and Ripley's MASS

dose.p

R Documentation

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)

Arguments

`obj`	A fitted model object of class inheriting from `"glm"`.
`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 (attribute "p" and standard error (attribute "SE") 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)

MASS documentation built on April 12, 2025, 1:56 a.m.