The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network Meta-analyses
Open accessAbstract
Background: Several reviews have noted shortcomings regarding the quality and reporting of network meta-analyses (NMAs). We suspect that this issue may be partially attributable to limitations in current NMA software which do not readily produce all of the output needed to satisfy current guidelines. Results: To better facilitate the conduct and reporting of NMAs, we have created an R package called “BUGSnet” (B ayesian inference U sing G ibbs S ampling to conduct a Net work meta-analysis). This R package relies upon Just Another Gibbs Sampler (JAGS) to conduct Bayesian NMA using a generalized linear model. BUGSnet contains a suite of functions that can be used to describe the evidence network, estimate a model and assess the model fit and convergence, assess the presence of heterogeneity and inconsistency, and output the results in a variety of formats including league tables and surface under the cumulative rank curve (SUCRA) plots. We provide a demonstration of the functions contained within BUGSnet by recreating a Bayesian NMA found in the second technical support document composed by the National Institute for Health and Care Excellence Decision Support Unit (NICE-DSU). We have also mapped these functions to checklist items within current reporting and best practice guidelines. Conclusion: BUGSnet is a new R package that can be used to conduct a Bayesian NMA and produce all of the necessary output needed to satisfy current scientific and regulatory standards. We hope that this software will help to improve the conduct and reporting of NMAs.
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Cites
Quantifying heterogeneity in a meta‐analysis
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JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling
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Automating network meta‐analysis
van Valkenhoef, G., Lu, G., de Brock, B., Hillege, H., Ades, A. E., & Welton, N. J. (2012) · Research Synthesis Methods · doi:10.1002/jrsm.1054 · Cited by 786
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Cited by
netmeta : An R Package for Network Meta-Analysis Using Frequentist Methods
Balduzzi, S., Rücker, G., Nikolakopoulou, A., Papakonstantinou, T., Salanti, G., Efthimiou, O., & Schwarzer, G. (2023) · Journal of Statistical Software · doi:10.18637/jss.v106.i02 · Cited by 532
“…R packages for Bayesian NMA: gemtc (Van Valkenhoef and Kuiper 2021), bnma (Seo and Schmid 2022), pc-netmeta (Lin, Zhang, Hodges, and Chu 2020), multinma (Phillippo 2022), nmaINLA (Guen-han, Friede, and Held 2018), bayesmeta (Röver 2020), BUGSnet (Béliveau, Boyne, Slater, Brenner, and Arora 2019).”
Joshi, G. P., Abdelmalak, B. B., Weigel, W. A., Harbell, M. W., Kuo, C. I., Soriano, S. G., Stricker, P. A., Tipton, T., Grant, M. D., Marbella, A. M., et al. (2023) · Anesthesiology · doi:10.1097/aln.0000000000004381 · Cited by 375
McIsaac, D. I., Kidd, G., Gillis, C., Branje, K., Al-Bayati, M., Baxi, A., Grudzinski, A. L., Boland, L., Veroniki, A.-A., Wolfe, D., et al. (2025) · BMJ · doi:10.1136/bmj-2024-081164 · Cited by 168
Management of Sarcopenia: A Network Meta-Analysis of Randomized Controlled Trials
Negm, A. M., Lee, J., Hamidian, R., Jones, C. A., & Khadaroo, R. G. (2022) · Journal of the American Medical Directors Association · doi:10.1016/j.jamda.2022.01.057 · Cited by 137
Oh, S., Choi, J., Han, D. H., & Kim, E. (2024) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-023-02174-z · Cited by 63
Metadata
- Authors
- Béliveau, A., Boyne, D. J., Slater, J., Brenner, D., & Arora, P.
- Venue
- BMC Medical Research Methodology
- Published
- 2019-10-22
- Volume
- 19
- Issue
- 1
- Pages
- 196-196
- ISSN
- 1471-2288 (ISSN-L)
- OpenAlex
- W2981452012
- Cited by
- 312
- References
- 31
- FWCI
- 14.52
- Type
- journal article
- Language
- en
- Open access
- gold
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