## Fitting a model with a common control
c.m1 <- drm(drymatter ~ dose, treatment, data = G.aparine,
pmodels = data.frame(treatment,treatment,1,treatment), fct = LL.4())
## Visual inspection of fit
plot(c.m1, broken = TRUE)
## Lack of fit test
modelFit(c.m1)
## Summary output
summary(c.m1)
## Predicted values with se and confidence intervals
predict(c.m1, interval = "confidence")
## Calculating the relative potency
SI(c.m1, c(50,50))
## Showing the relative potency as a
## function of the response level
relpot(c.m1)
relpot(c.m1, ci = "delta")
# appears constant!
## Response level in percent
relpot(c.m1, scale="percent")
## Fitting a reduced model
c.m2 <- drm(drymatter ~ dose, treatment, data = G.aparine,
pmodels = data.frame(1,treatment,1,treatment), fct = LL.4())
anova(c.m2, c.m1)
## Showing the relative potency
relpot(c.m2)
## Fitting the same model in a different parameterisation
c.m3<-drm(drymatter~dose, treatment, data=G.aparine,
pmodels=data.frame(treatment,treatment,1,treatment),fct=LL2.4())
SI(c.m3, c(50,50), logBase = exp(1))
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