Sequential Bayesian Data Synthesis for Mediation and Regression Analysis.

ABSTRACT: Science is an inherently cumulative process, and knowledge on a specific topic is organized through synthesis of findings from related studies. Meta-analysis has been the most common statistical method for synthesizing findings from multiple studies in prevention science and other fields. In recent years, Bayesian statistics have been put forth as another way to synthesize findings and have been praised for providing a natural framework for update existing knowledge with new data. This article presents a Bayesian method for cumulative science and describes a SAS macro %SBDS for synthesizing findings from multiple studies or multiple data sets from a single study using three different methods: meta-analysis using raw data, sequential Bayesian data synthesis, and a single-level analysis on p

SUBMITTER: Wurpts IC 

PROVIDER: S-EPMC9124629 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature