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.

Version:	1.2.3
Depends:	R (≥ 3.5.0), rjags (≥ 4-6)
Imports:	coda, Rdpack, grDevices, forestplot, metafor, lme4, methods
Suggests:	R.rsp
Published:	2022-10-02
DOI:	10.32614/CRAN.package.BayesCACE
Author:	Jinhui Yang [aut, cre], Jincheng Zhou [aut], James Hodges [ctb], Haitao Chu [ctb]
Maintainer:	Jinhui Yang <james.yangjinhui at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
SystemRequirements:	JAGS 4.x.y (http://mcmc-jags.sourceforge.net)
In views:	Bayesian
CRAN checks:	BayesCACE results

Documentation:

Reference manual:	BayesCACE.pdf
Vignettes:	BayesCACE paper

Downloads:

Package source:	BayesCACE_1.2.3.tar.gz
Windows binaries:	r-devel: BayesCACE_1.2.3.zip, r-release: BayesCACE_1.2.3.zip, r-oldrel: BayesCACE_1.2.3.zip
macOS binaries:	r-release (arm64): BayesCACE_1.2.3.tgz, r-oldrel (arm64): BayesCACE_1.2.3.tgz, r-release (x86_64): BayesCACE_1.2.3.tgz, r-oldrel (x86_64): BayesCACE_1.2.3.tgz
Old sources:	BayesCACE archive

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