mnma.run: Run multivariate network meta-analysis (NMA) anlaysis

In vandy10s/mnma: Multivariate Network Meta-Analysis (NMA) within a Bayesian Framework

Description

The function conducts bivariate NMA using a mnma.model object as an input. It uses OpenBUGS software (through the R2OpenBUGS package).

Usage

mnma.run(input, inits = NULL, n.iter = 5000, n.burnin = 2000,
  n.chains = 1, n.thin = 1, debug = FALSE, codaPkg = FALSE)

Arguments

input	mnma.model class data, which can be generated using mnma.model function
inits	a list of initial values for OpenBUGS model with n.chains elements; If inits=NULL (default), initial values are randomly generated by OpenBUGS.
n.iter	number of total iterations per chain (default: 5000)
n.burnin	length of burnin per chain (default: 2000)
n.chains	number of Markov chains (default: 1)
n.thin	thining rate (default: 1)
debug	if FALSE (default), OpenBUGS is closed automatically after running the mnma.run script. If TRUE, OpenBUGS remains open with additional information.
codaPkg	if FALSE (default), a bugs object is returned. Otherwise, file names of OpenBUGS output are returned with TRUE.

Value

mnma.result class bugs result. See bugs for details.

References

Efthimiou et al. (2015) Biostatistics 16(1):84-97 (doi: 10.1093/biostatistics/kxu030)

See Also

bugs

Examples

## Not run: 
# Run after data transformation using mnma.model function.
res <- mnma.run(data, n.iter=3000, n.burnin=1000)
names(res)
# provides mean, standard deviation, and percentile information about log odds ratio
res$summary

## End(Not run)

vandy10s/mnma documentation built on May 19, 2019, 8:24 a.m.