Bayesian Individual Patient Data Meta-Analysis using 'JAGS'
Convenient function to add results (i.e. combine mcmc.list)
bipd: A package for individual patient data meta-analysis using 'JAGS'
Find missing data pattern in a given data
Generate a simulated IPD-MA data for demonstration
Generate a simualted IPD-NMA data for demonstration
Generate a simulated IPD-MA data with systematically missing covariate...
Run the model using the ipd object with parallel computation
Run the model using the ipd object
Impute missing data in individual participant data with two treatments...
Make a (deft-approach) one-stage individual patient data meta-analysis...
Make an one-stage individual patient data meta-analysis object contain...
Make an one-stage individual patient data network meta-analysis object...
Calculate patient-specific treatment effect
We use a Bayesian approach to run individual patient data meta-analysis and network meta-analysis using 'JAGS'. The methods incorporate shrinkage methods and calculate patient-specific treatment effects as described in Seo et al. (2021) <DOI:10.1002/sim.8859>. This package also includes user-friendly functions that impute missing data in an individual patient data using mice-related packages.