| betaMod {MCPMod} | R Documentation |
Beta model
Description
The beta model is defined as
f(d,\theta)=E_0+E_{max}B(\delta_1,\delta_2)(d/scal)^{\delta_1}(1-d/scal)^{\delta_2}
where
B(\delta_1,\delta_2)=(\delta_1+\delta_2)^{\delta_1+\delta_2}/(\delta_1^{\delta_1} \delta_2^{\delta_2})
Usage
betaMod(dose, e0, eMax, delta1, delta2, scal)
Arguments
dose |
Dose variable |
e0 |
Placebo effect |
eMax |
Maximum effect |
delta1 |
delta1 parameter |
delta2 |
delta2 parameter |
scal |
Scale parameter (not estimated in the code) |
Details
The beta model is intended to capture non-monotone
dose-response relationships and is more flexible than the quadratic model.
The kernel of the beta model
function consists of the kernel of the density function of a beta
distribution on the interval [0,scal]. The parameter
scal is not estimated but needs to be set to a value
larger than the maximum dose via the argument scal.
Value
Response value
See Also
logistic, sigEmax,
linlog, linear, quadratic,
emax, exponential