LogisticLogNormal

LogisticLogNormal is the class for the usual logistic regression model with a bivariate normal prior on the intercept and log slope.

Usage

LogisticLogNormal(mean, cov, ref_dose = 1)

.DefaultLogisticLogNormal()

Arguments

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).

Details

The covariate is the natural logarithm of the dose \(x\) divided by the reference dose \(x*\), i.e.: $$logit[p(x)] = alpha0 + alpha1 * log(x/x*),$$ where \(p(x)\) is the probability of observing a DLT for a given dose \(x\). The prior $$(alpha0, log(alpha1)) ~ Normal(mean, cov).$$

Note

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

See also

ModelLogNormal, LogisticNormal, LogisticLogNormalSub, ProbitLogNormal, ProbitLogNormalRel, LogisticLogNormalMixture, DALogisticLogNormal.

Examples

my_model <- LogisticLogNormal(
  mean = c(-0.85, 1),
  cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
  ref_dose = 50
)
my_model
#> An object of class "LogisticLogNormal"
#> Slot "params":
#> An object of class "ModelParamsNormal"
#> Slot "mean":
#> [1] -0.85  1.00
#> 
#> Slot "cov":
#>      [,1] [,2]
#> [1,]  1.0 -0.5
#> [2,] -0.5  1.0
#> 
#> Slot "prec":
#>           [,1]      [,2]
#> [1,] 1.3333333 0.6666667
#> [2,] 0.6666667 1.3333333
#> 
#> 
#> Slot "ref_dose":
#> An object of class "positive_number"
#> [1] 50
#> 
#> Slot "datamodel":
#> function() {
#>       for (i in 1:nObs) {
#>         logit(p[i]) <- alpha0 + alpha1 * log(x[i] / ref_dose)
#>         y[i] ~ dbern(p[i])
#>       }
#>     }
#> <bytecode: 0x55c9545097d8>
#> <environment: 0x55c957498228>
#> 
#> Slot "priormodel":
#> function() {
#>       theta ~ dmnorm(mean, prec)
#>       alpha0 <- theta[1]
#>       alpha1 <- exp(theta[2])
#>     }
#> <bytecode: 0x55c954750ef8>
#> <environment: 0x55c957498458>
#> 
#> Slot "modelspecs":
#> function(from_prior) {
#>       ms <- list(mean = params@mean, prec = params@prec)
#>       if (!from_prior) {
#>         ms$ref_dose <- ref_dose
#>       }
#>       ms
#>     }
#> <bytecode: 0x55c9549ce9a8>
#> <environment: 0x55c957498458>
#> 
#> Slot "init":
#> function() {
#>       list(theta = c(0, 1))
#>     }
#> <bytecode: 0x55c954a74f88>
#> <environment: 0x55c957498458>
#> 
#> Slot "datanames":
#> [1] "nObs" "y"    "x"   
#> 
#> Slot "datanames_prior":
#> character(0)
#> 
#> Slot "sample":
#> [1] "alpha0" "alpha1"
#>