Title: Hierarchical Bayesian Benefit-Risk Assessment Using Discrete
Authors@R: c(person("Saurabh", "Mukhopadhyay", comment = "AbbVie Inc.",
role = c("aut"), email = "saurabh.mukhopadhyay@abbvie.com"),
role = c( "cre"), email = "stat.mukherjee@gmail.com"))
Description: Implements assessment of benefit-risk balance using Bayesian Discrete Choice Experiment. For more details see the article by Mukhopadhyay et al. (2019) <DOI:10.1080/19466315.2018.1527248>.
Note: Package 'R2jags' requires JAGS executable file installed
Author: Saurabh Mukhopadhyay [aut] (AbbVie Inc.),

Title: Hierarchical Bayesian Design for Clinical Trials
Description: Implements our hierarchical Bayesian design for randomized clinical trials.

Title: Hill/Bliss Independence Model for Combination Vaccines
Description: Calculate expected relative risk and proportion protected assuming normally distributed log10 transformed antibody dose for several component vaccine. Uses Hill models for each component which are combined under Bliss independence.
Packaged: Wed Sep 12 15:14:45 2007; faym

Description: Calculate expected relative risk and proportion protected
assuming normally distributed log10 transformed antibody dose
for several component vaccine. Uses Hill models for each
component which are combined under Bliss independence.

Description: Calculate expected relative risk and proportion protected assuming normally distributed log10 transformed antibody dose for a several component vaccine. Uses Hill models for each component which are combined under Bliss independence. See Saul and Fay, 2007 <DOI:10.1371/journal.pone.0000850>.

Title: Hierarchical Block Matrix Analysis
Description: A package for building hierarchical block matrices from association matrices and for performing multi-scale analysis. It specifically targets chromatin contact maps, generated from high-throughput chromosome conformation capture data, such as 5C and Hi-C, and provides methods for detecting movements and for computing chain hierarchy and region communicability across scales.