The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=BayesCACE
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.