Department of Psychology.
Psychol Trauma. 2016 Mar;8(2):249-57. doi: 10.1037/tra0000096.
Several contemporary researchers have noted the virtues of Bayesian methods of data analysis. Although debates continue about whether conventional or Bayesian statistics is the "better" approach for researchers in general, there are reasons why Bayesian methods may be well suited to the study of psychological trauma in particular. This article describes how Bayesian statistics offers practical solutions to the problems of data non-normality, small sample size, and missing data common in research on psychological trauma.
After a discussion of these problems and the effects they have on trauma research, this article explains the basic philosophical and statistical foundations of Bayesian statistics and how it provides solutions to these problems using an applied example.
Results of the literature review and the accompanying example indicates the utility of Bayesian statistics in addressing problems common in trauma research.
Bayesian statistics provides a set of methodological tools and a broader philosophical framework that is useful for trauma researchers. Methodological resources are also provided so that interested readers can learn more.
几位当代研究人员指出了贝叶斯数据分析方法的优点。尽管关于常规统计学和贝叶斯统计学哪种方法对一般研究人员来说更好的争论仍在继续，但贝叶斯方法特别适合心理创伤研究有其原因。本文描述了贝叶斯统计学如何为心理创伤研究中常见的数据非正态性、小样本量和缺失数据问题提供实际解决方案。
在讨论了这些问题及其对创伤研究的影响之后，本文解释了贝叶斯统计学的基本哲学和统计基础，以及它如何通过应用示例来解决这些问题。
文献综述和伴随的示例结果表明，贝叶斯统计学在解决创伤研究中常见问题方面具有实用性。
贝叶斯统计学为创伤研究人员提供了一套有用的方法学工具和更广泛的哲学框架。还提供了方法学资源，以便有兴趣的读者可以进一步了解。
