Package: BayesCACE 1.2.3

Jinhui Yang

BayesCACE: Bayesian Model for CACE Analysis

Performs CACE (Complier Average Causal Effect analysis) on either a single study or meta-analysis of datasets with binary outcomes, using either complete or incomplete noncompliance information. Our package implements the Bayesian methods proposed in Zhou et al. (2019) <doi:10.1111/biom.13028>, which introduces a Bayesian hierarchical model for estimating CACE in meta-analysis of clinical trials with noncompliance, and Zhou et al. (2021) <doi:10.1080/01621459.2021.1900859>, with an application example on Epidural Analgesia.

Authors:Jinhui Yang [aut, cre], Jincheng Zhou [aut], James Hodges [ctb], Haitao Chu [ctb]

BayesCACE_1.2.3.tar.gz
BayesCACE_1.2.3.tar.gz(r-4.7-any)BayesCACE_1.2.3.tar.gz(r-4.6-any)
BayesCACE_1.2.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BayesCACE/json (API)

# Install 'BayesCACE' in R:
install.packages('BayesCACE', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
  • c++– GNU Standard C++ Library v3
Datasets:
  • epidural_c - Meta-analysis data with full compliance information
  • epidural_ic - Meta-analysis data without full compliance information

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

jagscpp

2.00 score 359 downloads 16 exports 26 dependencies

Last updated from:4a9cf5282f. Checks:4 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK143
source / vignettesOK195
linux-release-x86_64OK147
wasm-releaseOK106

Exports:cace.meta.ccace.meta.iccace.studycoda.namescoda.samples.dicmodel.meta.cmodel.meta.icmodel.studyparse.varnameplt.acfplt.densityplt.forestplt.noncompplt.traceprior.metaprior.study

Dependencies:abindbackportsbootcheckmatecodadigestforestplotlatticelme4MASSmathjaxrMatrixmetadatmetaforminqanlmenloptrnumDerivpbapplyrbibutilsRcppRcppEigenRdpackreformulasrjagsrlang

BayesCACE paper

Rendered frommain.pdf.asisusingR.rsp::asison May 24 2026.

Last update: 2022-01-05
Started: 2022-01-05