LogisticKadane-class | R Documentation |
This is the logistic model in the parametrization of Kadane et al. (1980).
Let \rho_{0} = p(x_{min})
be the probability of a DLT and the minimum
dose x_{min}
, and let \gamma
be the dose with target toxicity
probability \theta
, i.e. p(\gamma) = \theta
. Then it can easily
be shown that the logistic regression model has intercept
\frac{\gamma logit(\rho_{0}) - x_{min} logit(\theta)}{\gamma -
x_{min}}
and slope
\frac{logit(theta) - logit(\rho_{0})}{\gamma - x_{min}}
The prior is a uniform distribution for \gamma
between x_{min}
and x_{max}
, and for \rho_{0}
as well a uniform distribution
between 0
and \theta
.
The slots of this class, required for creating the model, are the target toxicity, as well as the minimum and maximum of the dose range. Note that these can be different from the minimum and maximum of the dose grid in the data later on.
theta
the target toxicity probability \theta
xmin
the minimum of the dose range x_{min}
xmax
the maximum of the dose range x_{max}
model <- LogisticKadane(theta = 0.33,
xmin = 1,
xmax = 200)
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