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Data from an experiment where the chemicals acifluorfen and diquat tested on Lemna minor. The dataset has 7 mixtures used in 8 dilutions with three replicates and 12 common controls, in total 180 observations.
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A data frame with 180 observations on the following 3 variables.
dose
a numeric vector of dose values
pct
a numeric vector denoting the grouping according to the mixtures percentages
rgr
a numeric vector of response values (relative growth rates)
The dataset is analysed in Soerensen et al (2007). Hewlett's symmetric model seems appropriate for this dataset.
The dataset is kindly provided by Nina Cedergreen, Department of Agricultural Sciences, Royal Veterinary and Agricultural University, Denmark.
Soerensen, H. and Cedergreen, N. and Skovgaard, I. M. and Streibig, J. C. (2007) An isobole-based statistical model and test for synergism/antagonism in binary mixture toxicity experiments, Environmental and Ecological Statistics, 14, 383–397.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | ## Fitting the model with freely varying ED50 values
## Ooops: Box-Cox transformation is needed
acidiq.free <- drm(rgr ~ dose, pct, data = acidiq, fct = LL.4(),
pmodels = list(~factor(pct), ~1, ~1, ~factor(pct) - 1))
## Lack-of-fit test
modelFit(acidiq.free)
summary(acidiq.free)
## Plotting isobole structure
isobole(acidiq.free, xlim = c(0, 400), ylim = c(0, 450))
## Fitting the concentration addition model
acidiq.ca <- mixture(acidiq.free, model = "CA")
## Comparing to model with freely varying e parameter
anova(acidiq.ca, acidiq.free) # rejected
## Plotting isobole based on concentration addition -- poor fit
isobole(acidiq.free, acidiq.ca, xlim = c(0, 420), ylim = c(0, 450)) # poor fit
## Fitting the Hewlett model
acidiq.hew <- mixture(acidiq.free, model = "Hewlett")
## Comparing to model with freely varying e parameter
anova(acidiq.free, acidiq.hew) # accepted
summary(acidiq.hew)
## Plotting isobole based on the Hewlett model
isobole(acidiq.free, acidiq.hew, xlim = c(0, 400), ylim = c(0, 450)) # good fit
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