Description Usage Format Details Source References Examples
Quantal assay data from an experiment where the insectide deguelin was applied to Macrosiphoniella sanborni.
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A data frame with 6 observations on the following 4 variables.
dose
a numeric vector of doses applied
log10dose
a numeric vector of logarithm-transformed doses
r
a numeric vector contained number of dead insects
n
a numeric vector contained the total number of insects
The log-logistic model provides an inadequate fit.
The dataset is used in Nottingham and Birch (2000) to illustrate a semiparametric approach to dose-response modelling.
Morgan, B. J. T. (1992) Analysis of Quantal Response Data, London: Chapman \& Hall/CRC (Table 3.9, p. 117).
Notttingham, Q. J. and Birch, J. B. (2000) A semiparametric approach to analysing dose-response data, Statist. Med., 19, 389–404.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ## Log-logistic fit
deguelin.m1 <- drm(r/n~dose, weights=n, data=deguelin, fct=LL.2(), type="binomial")
modelFit(deguelin.m1)
summary(deguelin.m1)
## Loess fit
deguelin.m2 <- loess(r/n~dose, data=deguelin, degree=1)
## Plot of data with fits superimposed
plot(deguelin.m1, ylim=c(0.2,1))
lines(1:60, predict(deguelin.m2, newdata=data.frame(dose=1:60)), col = 2, lty = 2)
lines(1:60, 0.95*predict(deguelin.m2,
newdata=data.frame(dose=1:60))+0.05*predict(deguelin.m1, newdata=data.frame(dose=1:60), se = FALSE),
col = 3, lty=3)
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