Title: Bayesian Dose-Finding Designs using Pharmacokinetics(PK) for
Imports: ggplot2 (>= 2.0.0), dfcrm, methods, stats, graphics,
Packaged: 2017-06-29 12:46:16 UTC; artemistoumazi

Packaged: 2017-06-30 10:15:14 UTC; artemistoumazi

Title: Bayesian Dose-Finding Designs using Pharmacokinetics (PK) for
Copyright: stanmodels.R is copyright 2015, 2016 Trustees of Columbia
University. All other files are copyright French National
Institute of Health and Medical Research.
Packaged: 2017-09-28 11:37:31 UTC; artemistoumazi

Packaged: 2017-10-24 14:20:42 UTC; artemistoumazi

Authors@R: c(person("Artemis", "Toumazi", email = "artemis.toumazi@gmail.com", role = c("cre", "aut")),
person("Sarah", "Zohar", email = "sarah.zohar@inserm.fr", role = "aut"),
person("Moreno", "Ursino", email = "moreno.ursino@inserm.fr", role = "aut"),
person("Trustees of", "Columbia University", role = "cph", comment = "R/stanmodels.R"),
person("French National Institute of", "Health and Medical Research", role = "cph")
Copyright: stanmodels.R is copyright 2015, 2016, 2017 Trustees of
Columbia University. All other files are copyright French
National Institute of Health and Medical Research.
Description: Statistical methods involving PK measures are provided, in the dose allocation process during a Phase I clinical trials. These methods, proposed by Ursino et al, (2017) <doi:10.1002/bimj.201600084>, enter pharmacokinetics (PK) in the dose finding designs in different ways, including covariates models, dependent variable or hierarchical models. This package provides functions to generate data from several scenarios and functions to run simulations which their objective is to determine the maximum tolerated dose (MTD).
Packaged: 2018-03-25 14:26:09 UTC; artemistoumazi
Trustees of Columbia University [cph] (R/stanmodels.R),
French National Institute of Health and Medical Research [cph]

Packaged: 2018-07-29 19:35:52 UTC; artemistoumazi

Packaged: 2018-11-07 20:54:16 UTC; artemistoumazi

Title: Dichotomized Functional Response Regression
person("Fatemeh", "Asgari", email = "ft.asgari@sci.ui.ac.ir", role = c("aut", "cre")),
person("Saeed", "Hayati", email = "s.hayati@sci.ui.ac.ir", role = c("aut", "ctb"))
Description: Implementing Function-on-Scalar Regression model in which the response function is dichotomized and observed sparsely. This package provides smooth estimations of functional regression coefficients and principal components for the dichotomized functional response regression (dfrr) model.