Budworms <- data.frame(Logdose = rep(0:5, 2),
    Sex = factor(rep(c("M", "F"), each = 6)),
    Dead = c(1, 4, 9, 13, 18, 20, 0, 2, 6, 10, 12, 16))
Budworms$Alive <- 20 - Budworms$Dead
xyplot(Dead/20 ~ I(2^Logdose), Budworms, 
	 groups = Sex, panel = panel.superpose,
    xlab = "Dose", ylab = "Fraction dead",
	 key = list(text = list(c("Females:", "Males:")),
			points = 
			Rows(trellis.par.get("superpose.symbol"), 1:2),
			lines = 
			Rows(trellis.par.get("superpose.line"), 1:2),
			columns = 2, transparent = T),
    type="b")
bud.1 <- glm(cbind(Dead, Alive) ~ Sex*Logdose, 
				binomial, Budworms, trace=T, eps=1.0e-9)
bud.0 <- update(bud.1, .~.-Sex:Logdose)
attach(Budworms)
plot(2^Logdose, Dead/20, xlab = "Dose", 
	ylab = "Fraction dead", type = "n")
text(2^Logdose, Dead/20, c("+","o")[Sex], col = 5, 
	cex = 1.25)
newdat <- expand.grid(Logdose = seq(-0.1, 5.1, 0.1), Sex = levels(Sex))
newdat$Pr0 <- predict(bud.0, newdat, type = "response")
newdat$Pr1 <- predict(bud.1, newdat, type = "response")
ditch <- newdat$Logdose == 5.1 | newdat$Logdose < 0
newdat[ditch, ] <- NA
attach(newdat)
lines(2^Logdose, Pr1, col=4, lty = 4)
lines(2^Logdose, Pr0, col=3)
key(0,1,text = list(c("Females", "Males")),
	transparent = T, points = list(pch = c("+", "o"), col = 5))
key(0, 0.8, text = list(c("bud1", "bud0")), 
	lines = list(lty = c(4, 1), col = c(4, 3)), transparent = T)
detach("newdat")
detach("Budworms")