TITELogisticLogNormal

TITELogisticLogNormal is the class for TITE-CRM based on a logistic regression model using a bivariate normal prior on the intercept and log slope parameters.

This class inherits from the LogisticLogNormal.

Usage

TITELogisticLogNormal(weight_method = "linear", ...)

.DefaultTITELogisticLogNormal()

Arguments

weight_method

(string)
the weight function method: either linear or adaptive. This was used in Liu, Yin and Yuan's paper.

...

Arguments passed on to LogisticLogNormal

mean

(numeric)
the prior mean vector.

cov

(matrix)
the prior covariance matrix. The precision matrix prec is internally calculated as an inverse of cov.

ref_dose

(number)
the reference dose \(x*\) (strictly positive number).

Slots

weight_method

(string)
the weight function method: either linear or adaptive. This was used in Liu, Yin and Yuan's paper.

Note

Typically, end users will not use the .DefaultTITELogisticLogNormal() function.

See also

DALogisticLogNormal.

Examples

my_model <- TITELogisticLogNormal(
  mean = c(0, 1),
  cov = diag(2),
  ref_dose = 1,
  weight_method = "linear"
)

my_model1 <- TITELogisticLogNormal(
  mean = c(0, 1),
  cov = diag(2),
  ref_dose = 1,
  weight_method = "adaptive"
)