文章基本信息

标题：Bayesian analysis for social data: A step-by-step protocol and interpretation
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作者：Quan-Hoang Vuong ; Viet-Phuong La ; Minh-Hoang Nguyen 等
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