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Bayesian Analysis Reporting Guidelines
被引:191
|作者:
Kruschke, John K.
[1
]
机构:
[1] Indiana Univ, Dept Psychol & Brain Sci, Bloomington, IN 47405 USA
关键词:
POSTERIOR PREDICTIVE CHECKS;
SENSITIVITY-ANALYSIS;
JOURNALS;
METAANALYSIS;
PREVALENCE;
PSYCHOLOGY;
INFERENCE;
QUANTIFY;
VALUES;
TESTS;
D O I:
10.1038/s41562-021-01177-7
中图分类号:
B84 [心理学];
学科分类号:
04 ;
0402 ;
摘要:
Previous surveys of the literature have shown that reports of statistical analyses often lack important information, causing lack of transparency and failure of reproducibility. Editors and authors agree that guidelines for reporting should be encouraged. This Review presents a set of Bayesian analysis reporting guidelines (BARG). The BARG encompass the features of previous guidelines, while including many additional details for contemporary Bayesian analyses, with explanations. An extensive example of applying the BARG is presented. The BARG should be useful to researchers, authors, reviewers, editors, educators and students. Utilization, endorsement and promotion of the BARG may improve the quality, transparency and reproducibility of Bayesian analyses. The Review presents a comprehensive set of Bayesian analysis reporting guidelines (BARG), incorporating features of previous guidelines and extending these with many additional details for contemporary Bayesian analyses. It is accompanied by an extensive example of applying the BARG.
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页码:1282 / 1291
页数:10
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