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

Package details

AuthorJinhui Yang [aut, cre] (<>), Jincheng Zhou [aut] (<>), James Hodges [ctb], Haitao Chu [ctb] (<>)
MaintainerJinhui Yang <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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BayesCACE documentation built on Jan. 6, 2022, 5:08 p.m.