bipd-package {bipd}

bipd: A package for individual patient data meta-analysis using 'JAGS'

Description

A package for individual patient data meta-analysis using 'JAGS'

Details

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.

References

Audigier V, White I, Jolani S, et al. Multiple Imputation for Multilevel Data with Continuous and Binary Variables. Statistical Science. 2018;33(2):160-183. doi: 10.1214/18-STS646

Debray TPA, Moons KGM, Valkenhoef G, et al. Get real in individual participant data (IPD) meta-analysis: a review of the methodology. Res Synth Methods. 2015;6(4):293-309. doi: 10.1002/jrsm.1160

Dias S, Sutton AJ, Ades AE, et al. A Generalized Linear Modeling Framework for Pairwise and Network Meta-analysis of Randomized Controlled Trials. Medical Decision Making. 2013;33(5):607-617. doi: 10.1177/0272989X12458724

Fisher DJ, Carpenter JR, Morris TP, et al. Meta-analytical methods to identify who benefits most from treatments: daft, deluded, or deft approach?. BMJ. 2017;356:j573. doi: 10.1136/bmj.j573

O'Hara RB, Sillanpaa MJ. A review of Bayesian variable selection methods: what, how and which. Bayesian Anal. 2009;4(1):85-117. doi: 10.1214/09-BA403

Riley RD, Debray TP, Fisher D, et al. Individual participant data meta-analysis to examine interactions between treatment effect and participant-level covariates: Statistical recommendations for conduct and planning. Stat Med. 2020:39(15):2115-2137. doi: 10.1002/sim.8516

Seo M, White IR, Furukawa TA, et al. Comparing methods for estimating patient-specific treatment effects in individual patient data meta-analysis. Stat Med. 2021;40(6):1553-1573. doi: 10.1002/sim.8859