bda (version 10.1.9)

ld50.logit: Predict Doses for Binomial Assay model (using counts)

Description

Calibrate binomial assays, generalizing the calculation of LD50 based on a logistic regression model.

Usage

ld50.logit(ndead, ntotal, dose, cf = 1:2, p = 0.5)

Arguments

ndead

A vector of number of failures.

ntotal

Total number of trials.

dose

A vector of dosages.

cf

The terms in the coefficient vector giving the intercept and coefficient of (log-)dose

p

Probabilities at which to predict the dose needed.

References

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

Examples

# NOT RUN {
ldose <- rep(0:5, 2)
numdead <- c(1, 4, 9, 13, 18, 20, 0, 2, 6, 10, 12, 16)
n=20

ld50.logit(numdead,n,ldose,p = 0.5)
# }