关于
This skill enables users to implement sophisticated Bayesian meta-analysis techniques directly within their workflow. It covers a wide spectrum of models, from simple fixed and random effects to complex network meta-analyses (NMA) and publication bias selection models. By offering standardized code patterns in both Stan and JAGS, it facilitates robust statistical modeling, handling of binary outcomes via log-odds, and the calculation of critical metrics like heterogeneity (I²) and treatment rankings. It is an essential resource for biostatisticians and data scientists performing systematic reviews or evidence-based research.
