DualEndpointOld-class | R Documentation |
todo: describe the model
mu
For the probit toxicity model, mu
contains the prior mean
vector
Sigma
For the probit toxicity model, contains the prior covariance matrix
sigma2betaW
For the biomarker model, contains the prior variance
factor of the random walk prior. If it is not a single number, it can also
contain a vector with elements a
and b
for the inverse-gamma prior
on sigma2betaW
.
sigma2W
Either a fixed value for the biomarker variance, or a vector
with elements a
and b
for the inverse-gamma prior parameters.
rho
Either a fixed value for the correlation (between -1 and 1), or a
vector with elements a
and b
for the Beta prior on the
transformation kappa = (rho + 1) / 2, which is in (0, 1). For example,
a=1,b=1
leads to a uniform prior on rho.
useRW1
for specifying the random walk prior on the biomarker level: if
TRUE
, RW1 is used, otherwise RW2.
useFixed
a list with logical value for each of the three parameters
sigma2betaW
, sigma2W
and rho
indicating whether
a fixed value is used or not.
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