SI(object, percVec, compMatch = NULL, od = FALSE, reverse = FALSE,
ci = c("none", "delta", "fieller", "fls"),
level = ifelse(!(ci=="none"), 0.95, NULL),
reference = c("control", "upper"),
type = c("relative", "absolute"), logBase = NULL,
display = TRUE, ...)
relpot(object, plotit = TRUE, compMatch = NULL, percVec = NULL, ci = "none",
type = c("relative", "absolute"), scale = c("original", "percent", "unconstrained"), ...)
SI
: additional arguments to the function doing the calculations.
For instance the upper limit for the bisection method
needs to be larger than the ED values used in the required relative pontency.
In relpot
: additiorelpot
is a convenience function, which is useful for assessing how the relative potency
changes as a function of the response level (eg for plotting as outlined in Ritz et al (2006)).
Fieller's theorem is incorporated using the formulas Kotz and Johnson (1983) and Finney (1978).
For objects of class 'braincousens' or 'mlogistic' the additional argument may be the 'upper' argument
or the 'interval' argument. The 'upper' argument specifies the upper limit of the bisection method.
The upper limits needs to be larger than the EDx level to be calculated. The default limit is 1000.
The 'interval' argument should specify a rough interval in which the dose
yielding the maximum hormetical response lies. The default interval is 'c(0.001, 1000)'.
Notice that the lower limit should not be set to 0 (use something like 1e-3, 1e-6, ...).ED.drc
(for calculating effective doses) and
relpot
(for displaying relative potencies).m1 <- drm(SLOPE~DOSE, CURVE, data = spinach, fct = LL.4())
SI(m1, c(50,50))
SI(m1, c(10,50))
SI(m1, c(10,50), reverse = TRUE)
## Relative potency of two herbicides
m2 <- drm(DryMatter~Dose, Herbicide,
data = S.alba, fct = LL.3())
SI(m2, c(50, 50))
SI(m2, c(50, 50), ci = "delta")
SI(m2, c(50, 50), ci = "fieller")
## Comparison based on absolute
## response level
m3 <- drm(SLOPE~DOSE, CURVE,
data = spinach, fct = LL.4())
SI(m3, c(0.5,0.5), c(2,4), type="a", ci="fieller")
SI(m3, c(55,80), c(2,4))
# same comparison using a relative response level
## Relative potency transformed from log scale
m4 <- drm(drymatter~log(dose), treatment, data=G.aparine[-c(1:40), ],
pmodels = data.frame(treatment,treatment,1,treatment), fct = LL2.4())
SI(m4, c(50,50), ci="fls", logBase=exp(1))
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