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.