knitr, shiny, anoint, rmarkdown, pander, shinythemes, DT

knitr, shiny, anoint, rmarkdown, pander, shinythemes, DT,
testthat

rstan (>= 2.17.3), rstantools (>= 1.5.0), survival, loo

It is vital to assess the heterogeneity of treatment effects
(HTE) when making health care decisions for an individual patient or a group
of patients. Nevertheless, it remains challenging to evaluate HTE based
on information collected from clinical studies that are often designed and
conducted to evaluate the efficacy of a treatment for the overall population.
The Bayesian framework offers a principled and flexible approach to estimate
and compare treatment effects across subgroups of patients defined by their
characteristics. This package allows users to explore a wide range of Bayesian
HTE analysis models, and produce posterior inferences about HTE. See Wang et al.
(2018) <10.18637/jss.v085.i07> for further details.

It is vital to assess the heterogeneity of treatment effects
(HTE) when making health care decisions for an individual patient or a group
of patients. Nevertheless, it remains challenging to evaluate HTE based
on information collected from clinical studies that are often designed and
conducted to evaluate the efficacy of a treatment for the overall population.
The Bayesian framework offers a principled and flexible approach to estimate
and compare treatment effects across subgroups of patients defined by their
characteristics. This package allows users to explore a wide range of Bayesian
HTE analysis models, and produce posterior inferences about HTE. See Wang et al.
(2018) <DOI:10.18637/jss.v085.i07> for further details.
rstan (>= 2.18.1), rstantools (>= 1.5.0), survival, loo
knitr, shiny, rmarkdown, pander, shinythemes, DT, testthat

Bioavability and Bioequivalence data analysis with crossover design (ABE)
Hsin-ya Lee <hsinyalee@gmail.com>, Yung-jin Lee <pkpd.taiwan@gmail.com>
A menu-driven package for bioavability andbBioequivalence data analysis including sample size estimation, noncompartment analysis (NCA) and generalized linear model (GLM)