1d:T67a,# Decision function for the choice of variance (sigmaHI or sigmaLI) in the adaptive prior variance calibration. Algorithm of the decision function for the choice of variance (sigmaHI or sigmaLI) in the adaptive prior variance calibration. ```r 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, . Zhang J., Braun T., and J. Taylor. (2013) Adaptive prior variance calibration in the bayesian continual reassessment method. Stat. Med. ## Author(s) Artemis Toumazi artemis.toumazi@gmail.com , Caroline Petit caroline.petit@crc.jussieu.fr , Sarah Zohar sarah.zohar@inserm.fr ## See Also `doseChoice` ## Examples ```r 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) ```1e:T49a,M7.49933 0.25C3.49635 0.25 0.25 3.49593 0.25 7.50024C0.25 10.703 2.32715 13.4206 5.2081 14.3797C5.57084 14.446 5.70302 14.2222 5.70302 14.0299C5.70302 13.8576 5.69679 13.4019 5.69323 12.797C3.67661 13.235 3.25112 11.825 3.25112 11.825C2.92132 10.9874 2.44599 10.7644 2.44599 10.7644C1.78773 10.3149 2.49584 10.3238 2.49584 10.3238C3.22353 10.375 3.60629 11.0711 3.60629 11.0

priorChoice function