ProbitLogNormal-class | R Documentation |
ProbitLogNormal
ProbitLogNormal
is the class for probit regression model with a
bivariate normal prior on the intercept and log slope.
ProbitLogNormal(mean, cov, ref_dose = 1)
.DefaultProbitLogNormal()
mean |
( |
cov |
( |
ref_dose |
( |
The covariate is the natural logarithm of dose x
divided by a
reference dose x*
, i.e.:
probit[p(x)] = alpha0 + alpha1 * log(x/x*),
where p(x)
is the probability of observing a DLT for a given dose x
.
The prior
(alpha0, log(alpha1)) ~ Normal(mean, cov).
This model is also used in the DualEndpoint
classes, so this class
can be used to check the prior assumptions on the dose-toxicity model, even
when sampling from the prior distribution of the dual endpoint model is not
possible.
Typically, end users will not use the .DefaultProbitLogNormal()
function.
ModelLogNormal
, LogisticNormal
, LogisticLogNormal
,
LogisticLogNormalSub
, ProbitLogNormalRel
.
my_model <- ProbitLogNormal(
mean = c(-0.85, 1),
cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
ref_dose = 7.2
)
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