Data are from an experiment, comparing the potency of the two herbicides glyphosate and bentazone in white mustard Sinapis alba.

data(S.alba)

Format

A data frame with 68 observations on the following 3 variables.

Dose

a numeric vector containing the dose in g/ha.

Herbicide

a factor with levels Bentazone Glyphosate (the two herbicides applied).

DryMatter

a numeric vector containing the response (dry matter in g/pot).

Details

The lower and upper limits for the two herbicides can be assumed identical, whereas slopes and ED50 values are different (in the log-logistic model).

Source

Christensen, M. G. and Teicher, H. B., and Streibig, J. C. (2003) Linking fluorescence induction curve and biomass in herbicide screening, Pest Management Science, 59, 1303--1310.

Examples

# NOT RUN {
library(drc)

## Fitting a log-logistic model with
##  common lower and upper limits
S.alba.LL.4.1 <- drm(DryMatter~Dose, Herbicide, data=S.alba, fct = LL.4(),
pmodels=data.frame(Herbicide,1,1,Herbicide))
summary(S.alba.LL.4.1)

## Applying the optimal transform-both-sides Box-Cox transformation
## (using the initial model fit)  
S.alba.LL.4.2 <- boxcox(S.alba.LL.4.1, method = "anova")
summary(S.alba.LL.4.2)

## Plotting fitted regression curves together with the data
plot(S.alba.LL.4.2)
# }