dose.p

0th

Percentile

Predict Doses for Binomial Assay model

Calibrate binomial assays, generalizing the calculation of LD50.

Keywords
models, regression
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.

Aliases
  • dose.p
  • print.glm.dose
Examples
# NOT RUN {
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)
# }
Documentation reproduced from package MASS, version 7.3-51.1, License: GPL-2 | GPL-3

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