Bayesian Model for CACE Analysis
Generate posterior samples in mcmc.list format
Bayesian hierarchical model code for CACE meta-analysis with complete ...
Bayesian hierarchical models for CACE meta-analysis with complete comp...
Bayesian hierarchical models for CACE meta-analysis with incomplete co...
CACE analysis for a single study, or a two-step approach for meta-anal...
Get names of node array
Bayesian hierarchical model code for CACE meta-analysis with complete ...
Model code of CACE analysis for a single study, or a two-step approach...
Parse strings of specific form
this plot function creates an acf plot
this plot function creates a density plot
this plot function makes a forest plot.
Plotting noncompliance rates for a given dataset
this plot function creates a traceplot
The function returns a custom string that specifies part of the model.
The function returns a custom string that specifies part of the model ...
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.