For three days, moths of the tobacco budworm (Heliothis virescens) were exposed to doses of the pyrethroid trans-cypermethrin.

data(H.virescens)

Format

A data frame with 12 observations on the following 4 variables.

dose

a numeric vector of dose values (\(\mu g\))

numdead

a numeric vector of dead or knocked-down moths

total

a numeric vector of total number of moths

sex

a factor with levels F M denoting a grouping according to sex

Details

In Venables and Ripley (2002), these data are analysed using a logistic regression with base-2 logarithm of dose as explanatory variable.

Source

Venables, W. N. and Ripley, B. D (2002) Modern Applied Statistics with S, New York: Springer (fourth edition).

Examples

# NOT RUN {
library(drc)

## Fitting dose-response model (log-logistic with common slope)
Hv.m1 <- drm(numdead/total~dose, sex, weights = total, data = H.virescens, fct = LL.2(),
pmodels = list(~ 1, ~ sex - 1), type = "binomial")
summary(Hv.m1)

## Fitting the same model as in Venables and Riply (2002)
Hv.m2 <- glm(cbind(numdead, total-numdead) ~ sex + I(log2(dose)) - 1, data = H.virescens,
family = binomial)

## Comparing the fits
logLik(Hv.m1)
logLik(Hv.m2)

## Estimated ED values (matching those given in MASS)
ED(Hv.m1, c(25, 50, 75))
# }