首页    期刊浏览 2024年10月05日 星期六
登录注册

文章基本信息

  • 标题:Bayesian analysis for social data: A step-by-step protocol and interpretation
  • 本地全文:下载
  • 作者:Quan-Hoang Vuong ; Viet-Phuong La ; Minh-Hoang Nguyen
  • 期刊名称:MethodsX
  • 印刷版ISSN:2215-0161
  • 电子版ISSN:2215-0161
  • 出版年度:2020
  • 卷号:7
  • 页码:1-17
  • DOI:10.1016/j.mex.2020.100924
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe paper proposes Bayesian analysis as an alternative approach for the conventional frequentist approach in analyzing social data. A step-by-step protocol of how to implement Bayesian multilevel model analysis with social data and how to interpret the result is presented. The article used a dataset regarding religious teachings and behaviors of lying and violence as an example. An analysis is performed using R statistical software and a bayesvl R package, which offers a network-structured model construction and visualization power to diagnose and estimate results.•The paper provides guidance for conducting a Bayesian multilevel analysis in social sciences through constructing directed acyclic graphs (DAGs, or "relationship trees") for different models, basic and more complex ones.•The method also illustrates how to visualize Bayesian diagnoses and simulated posterior.•The interpretations of visualized diagnoses and simulated posteriors of Bayesian inference are also discussed.Graphical abstractDisplay Omitted
  • 关键词:Bayesian statistics;Social data;Markov chain monte carlo (MCMC);Bayesvl
国家哲学社会科学文献中心版权所有