Data are from an experiment, comparing the potency of the two herbicides glyphosate and bentazone in white mustard Sinapis alba.
A data frame with 68 observations on the following 3 variables.
a numeric vector containing the dose in g/ha.
a factor with levels
Glyphosate (the two herbicides applied).
a numeric vector containing the response (dry matter in g/pot).
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).
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.
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## 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)
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