BeetleMortality {glmx} | R Documentation |
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)