predict
can now return standard errors and prediction intervals.x
-axis of the plot.plot
when doses were not previously sorted.x
-axis of the plot
when data contained zeros.plot_data
to
FALSE
(default TRUE
).It is now possible to fit models using either the log-dose or the dose scale.
To accommodate this extension it was necessary to change the default model parameterization, which now follows that of the Emax model (Macdougall, 2006).
Briefly, the 5-parameter logistic function is now defined as
alpha + delta / (1 + nu * exp(-eta * (x - phi)))^(1 / nu)
Parameter alpha
is the value of the function when x
approaches -Inf
.
Parameter delta
is the (signed) height of the curve.
Parameter eta > 0
represents the steepness (growth rate) of the curve.
Parameter phi
is related to the mid-value of the function.
Parameter nu
affects near which asymptote maximum growth occurs.
Similarly, the newly implemented log-logistic function (when x >= 0
) is
defined as
alpha + delta * (x^eta / (x^eta + nu * phi^eta))^(1 / nu)
Check the vignette (vignette("drda", package = "drda")
) or the help page (help(drda)
) to know more about the available models.
Here is a change log from previous version:
effective_dose
function for estimating effective doses.First public release.
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