Hierarchical Selection Models with Applications in Meta-Analysis
层级选择模型及其在元分析中的应用
Hierarchical selection models are introduced and shown to be useful in meta-analysis. These models combine the use of hierarchical models, allowing investigation of variability both within and between studies, and weight functions, allowing modeling of nonrandomly selected studies. Markov chain Monte Carlo (MCMC) methods are used to estimate the hierarchical selection model. This is first illustrated for known weight functions, and then extended to allow for estimation of…