对于假设测试的安贝叶斯因子
Karl Christoph Klauer1, Constantin G Meyer-Grant2, David Kellen3
1Department of Psychology, Albert-Ludwigs-Universität Freiburg, 79085, Freiburg, Germany. christoph.klauer@psychologie.uni-freiburg.de.
Psychonomic bulletin & review
|November 25, 2024
概括
研究人员为统计假设测试引入了新的贝叶斯因子,为t测试和回归等常见分析提供了比默认方法的改进. 这些替代贝叶斯因子可以通过R包访问.
科学领域:
- 统计 统计 统计 统计
- 心理学研究方法论 心理学研究方法论
背景情况:
- 默认的贝叶斯因子在假设测试中很受欢迎.
- 违约先例的某些特征被认为是不可信的.
- 现有的方法可能无法完全满足心理学研究的需求.
研究的目的:
- 开发用于常见统计分析的替代贝叶斯因子.
- 解决默认贝叶斯因子的局限性,特别是先前的规范.
- 为研究人员提供一个可访问的计算工具.
主要方法:
- 为单样和双样t测试,回归和ANOVA衍生出替代贝叶斯因子.
- 使用基于测试统计的贝叶斯因子框架.
- 开发了一个R包,用于方便的计算.
主要成果:
- 替代贝叶斯因子展示了可取的理论和实践特性.
- 这些因素减轻了先前违约的不可思议特征.
- 在默认/替代贝叶斯因子和基于测试统计的贝叶斯因子之间证明了等价性.
结论:
- 替代贝叶斯因子为心理研究中的假设测试提供了一个强大的替代方案.
- 基于测试统计的贝叶斯因子提供了一个一般的计算方法.
- "R包"有助于采用这些先进的统计方法.
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