Bayesian Network Meta-Analysis using 'JAGS'
rjags (>= 4-6), graphics, stats, utils, coda (>= 0.13),
ggplot2, grid, igraph
c(
person("Michael", "Seo", email = "swj8874@gmail.com", role = c("aut", "cre")),
person("Christopher", "Schmid", email = "christopher_schmid@brown.edu", role = "aut"))
Network meta-analyses using Bayesian framework following Dias et al. (2013) <DOI:10.1177/0272989X12458724>. Based on the data input, creates prior, model file, and initial values needed to run models in 'rjags'. Able to handle binomial, normal and multinomial arm-based data. Can handle multi-arm trials and includes methods to incorporate covariate and baseline risk effects. Includes standard diagnostics and visualization tools to evaluate the results.
Michael Seo [aut, cre],
Christopher Schmid [aut]

Network meta-analyses using Bayesian framework following Dias et al. (2013) <DOI:10.1177/0272989X12458724>. Based on the data input, creates prior, model file, and initial values needed to run models in 'rjags'. Able to handle binomial, normal and multinomial arm-level data. Can handle multi-arm trials and includes methods to incorporate covariate and baseline risk effects. Includes standard diagnostics and visualization tools to evaluate the results.

An Implementation of Sensitivity Analysis in Bayesian Networks
c(
person("Manuele", "Leonelli", email = "manuele.leonelli@ie.edu", role = c("aut","cre")),
person("Ramsiya", "Ramanathan", email = "ramsiya.ramanathan@studio.unibo.it", role = "aut"),
person("Rachel", "Wilkerson", email = "R.L.Wilkerson@warwick.ac.uk", role = "aut"))
An implementation of sensitivity and robustness methods in Bayesian networks in R. It includes methods to perform parameter variations via a variety of co-variation schemes, to compute sensitivity functions and to quantify the dissimilarity of two Bayesian networks via distances and divergences. It further includes diagnostic methods to assess the goodness of fit of a Bayesian networks to data, including global, node and parent-child monitors. References: H. Chan, A. Darwiche (2002) <doi:10.1613/jair.967>; R.G. Cowell, R.J. Verrall, Y.K. Yoon (2007) <doi:10.1111/j.1539-6975.2007.00235.x>; C. Goergen, M. Leonelli (2020) <ArXiv:1809.10794>.
bnlearn, DiagrammeR, dplyr, ggplot2, gRain, gRbase, graphics,
gridExtra, matrixcalc, purrr, RColorBrewer, reshape2, rlang,
tidyr
Manuele Leonelli [aut, cre],
Ramsiya Ramanathan [aut],
Rachel Wilkerson [aut]