| TwoDrugsCombo-class | R Documentation |
TwoDrugsComboTwoDrugsCombo is the class for a two-drug combination regression model with
fixed priors for the two single-agent dose-toxicity models and an additional
interaction parameter.
TwoDrugsCombo(single_models, gamma = 0, tau = 1, log_normal_eta = FALSE)
.DefaultTwoDrugsCombo()
single_models |
( |
gamma |
( |
tau |
( |
log_normal_eta |
( |
Let p(x_1, x_2) be the probability of DLT at the dose
combination (x_1, x_2). The model combines two single-agent models
with an interaction term:
\textrm{odds}(p(x_1, x_2)) = \textrm{odds}(p_0(x_1, x_2)) *
\exp\left(\eta * I(x_1, x_2)\right),
where p_0(x_1, x_2) = 1 - (1 - p_1(x_1))(1 - p_2(x_2)) and each
single-agent probability follows a model p_j(x_j). The normalized dose
\tilde{x}_j is extracted from the single-agent model's dose covariate,
e.g. x_j / x_j^{*}, x_j - x_j^{*}, or x_j.
The interaction parameter \eta has either a normal prior or, if
log_normal_eta = TRUE, a log-normal prior.
single_models(list)
named list of length 2 containing single-agent GeneralModel objects,
one per drug. Each model must use nObs, y, and x as data inputs and
contain a Bernoulli likelihood for y in its datamodel.
ref_dose(numeric)
optional reference doses extracted from single_models, if provided.
drug_names(character)
the names of the two drugs.
gamma(numeric)
prior mean parameter for the interaction term.
tau(numeric)
prior precision parameter for the interaction term.
log_normal_eta(flag)
should the interaction term use a log-normal prior?
Typically, end users will not use the .DefaultTwoDrugsCombo() function.
LogisticLogNormal, DataCombo.
my_model <- TwoDrugsCombo(
single_models = list(
drug1 = LogisticLogNormal(
mean = c(-0.85, 1),
cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
ref_dose = 10
),
drug2 = LogisticLogNormal(
mean = c(-0.7, 0.8),
cov = matrix(c(1.1, -0.3, -0.3, 0.9), nrow = 2),
ref_dose = 20
)
),
gamma = 0,
tau = 1
)
my_model
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