BeetleMortality: Bliss (1935) Beetle Mortality Data

In glmx: Generalized Linear Models Extended

Bliss (1935) Beetle Mortality Data

Description

Mortality of adult flour beetle after five hours' exposure to gaseous carbon disulphide.

Usage

data("BeetleMortality")

Format

A data frame containing 8 observations on 3 variables.

dose

numeric. \log_{10} dose.

died

integer. Number killed.

n

integer. Number exposed.

Details

The data originates from Bliss (1935) and has been reanalyzed frequently.

Source

Bliss CI (1935). “The Calculation of the Dosage-Mortality Curve.” Annals of Applied Biology, 22, 134–167.

References

Aranda-Ordaz F (1981). “On Two Families of Transformations to Additivity for Binary Response Data.” Biometrika, 68, 357–363.

Hauck W (1990). “Choice of Scale and Asymmetric Logistic Models.” Biometrical Journal, 32, 79–86

Prentice RL (1976). “A Generalization of the Probit and Logit Methods for Dose Response Curves.” Biometrics, 38, 761–768.

Pregibon D (1980). “Goodness of Link Tests for Generalized Linear Models.” Journal of the Royal Statistical Society C, 29, 15–23.

Examples

## data
data("BeetleMortality", package = "glmx")

## various standard binary response models
m <- lapply(c("logit", "probit", "cloglog"), function(type)
  glm(cbind(died, n - died) ~ dose, data = BeetleMortality, family = binomial(link = type)))

## visualization
plot(I(died/n) ~ dose, data = BeetleMortality)
lines(fitted(m[[1]]) ~ dose, data = BeetleMortality, col = 2)
lines(fitted(m[[2]]) ~ dose, data = BeetleMortality, col = 3)
lines(fitted(m[[3]]) ~ dose, data = BeetleMortality, col = 4)

glmx documentation built on Sept. 11, 2024, 8:10 p.m.