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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.
Getting started
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Package details |
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| Author | Jinhui Yang [aut, cre] (<https://orcid.org/0000-0001-8322-1121>), Jincheng Zhou [aut] (<https://orcid.org/0000-0003-2641-2495>), James Hodges [ctb], Haitao Chu [ctb] (<https://orcid.org/0000-0003-0932-598X>) |
| Maintainer | Jinhui Yang <james.yangjinhui@gmail.com> |
| License | GPL (>= 2) |
| Version | 1.2.3 |
| Package repository | View on CRAN |
| Installation |
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