dfped (version 1.1)

priorChoice: Decision function for the choice of variance (sigmaHI or sigmaLI) in the adaptive prior variance calibration.

Description

Algorithm of the decision function for the choice of variance (sigmaHI or sigmaLI) in the adaptive prior variance calibration.

Usage

priorChoice(tox, givenDose, skeletonTox, lesb)

Arguments

tox

The vector of toxicity.

givenDose

The vector of doses given to patients so far.

skeletonTox

Skeleton of toxicity for the BMA bivariate CRM or the bivariate CRM model.

lesb

A vector containing the parameters b; (resp. 0 <- b1 < ... < bk < 1).

References

Petit, C., et al, (2016) Unified approach for extrapolation and bridging of adult information in early phase dose-finding paediatric studies, Statistical Methods in Medical Research, <doi:10.1177/0962280216671348>.

Zhang J., Braun T., and J. Taylor. (2013) Adaptive prior variance calibration in the bayesian continual reassessment method. Stat. Med.

See Also

doseChoice

Examples

# NOT RUN {
tox <-  c(0.10, 0.21, 0.33, 0.55, 0.76)
givenDose <- 2

skeleton_tox1 <- c(0.10, 0.21, 0.33, 0.55, 0.76)
skeleton_tox2 <- c(0.21, 0.33, 0.55, 0.76, 0.88)
skeleton_tox3 <- c(0.05, 0.10, 0.21, 0.33, 0.55)
skeleton_tox4 <- c(0.025, 0.05,0.1, 0.21, 0.33)
skeleton_tox5 <- c(0.0125, 0.025, 0.05,0.1, 0.21)

skeletonTox <-  data.frame(skeleton_tox1, skeleton_tox2, skeleton_tox3, 
                           skeleton_tox4, skeleton_tox5)

lesb <- c(0.10, 0.16, 0.23, 0.25, 0.30)
priorChoice(tox, givenDose, skeletonTox, lesb)
# }