DualEndpointBeta-class | R Documentation |
This class extends the DualEndpoint
class. Here the
dose-biomarker relationship f(x)
is modelled by a parametric, rescaled
beta density function:
f(x) = E_{0} + (E_{max} - E_{0}) * Beta(\delta_{1}, \delta_{2}) *
(x/x^{*})^{\delta_{1}} * (1 - x/x^{*})^{\delta_{2}}
where x^{*}
is the maximum dose (end of the dose range to be
considered), \delta_{1}
and \delta_{2}
are the two beta
parameters, and E_{0}
and E_{max}
are the minimum and maximum
levels, respectively. For ease of interpretation, we parametrize with
\delta_{1}
and the mode of the curve instead, where
mode = \delta_{1} / (\delta_{1} + \delta_{2}),
and multiplying this with x^{*}
gives the mode on the dose grid.
All parameters can currently be assigned uniform distributions or be fixed
in advance. Note that E0
and Emax
can have negative values or uniform
distributions reaching into negative range, while delta1
and mode
must be positive or have uniform distributions in the positive range.
E0
either a fixed number or the two uniform distribution parameters
Emax
either a fixed number or the two uniform distribution parameters
delta1
either a fixed number or the two uniform distribution parameters
mode
either a fixed number or the two uniform distribution parameters
refDoseBeta
the reference dose x^{*}
(note that this is different from
the refDose
in the inherited DualEndpoint
model)
model <- DualEndpointBeta(E0 = c(0, 100),
Emax = c(0, 500),
delta1 = c(0, 5),
mode = c(1, 15),
refDose=10,
useLogDose=TRUE,
refDoseBeta = 1000,
mu = c(0, 1),
Sigma = matrix(c(1, 0, 0, 1), nrow=2),
sigma2W = c(a=0.1, b=0.1),
rho = c(a=1, b=1))
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