集合中的替代变量与目标变量有不同的关联吗? 统计测试和实践建议,以处理依赖关系的相关性
1Departamento de Metodología, Facultad de Psicología, Universidad Complutense, Madrid, Spain.
概括
比较依赖性相关性需要仔细的统计测试. 这项研究发现,在评估重叠相关性之间的差异的十种方法中,有五种方法是不可靠的,而剩下的五种方法是可以接受的,但不是普遍可靠的.
科学领域:
- 统计 统计 统计 统计
- 心理测量 心理测量 心理测量
- 行为科学 行为科学
背景情况:
- 两变相关性分析在研究中很常见.
- 比较依赖性相关性往往依赖于非正式的方法或个别显著性测试.
- 对于与重叠变量相关的依赖关系之间的差异,现有的统计测试并不总是被很好地理解或正确地应用.
研究的目的:
- 评估十项统计测试的准确性,功率和稳定性,用于比较两个有重叠变量的依赖相关性.
- 为这个特定的比较场景确定可靠和适当的统计方法.
- 为选择测试的研究人员提供实际指导.
主要方法:
- 使用模拟方法来评估测试性能.
- 在各种条件下计算出经验I型错误率 (准确性).
- 统计能力和对非正常性的稳定性也得到了评估.
- 我们比较了十种不同的依赖相关性统计测试.
主要成果:
- 在十种测试方法中,有五种方法显示了不可接受的经验I型错误率,明显偏离了名义的α水平.
- 其余的五项测试被认为是可以接受的,在准确性,功率和稳定性标准上表现相似.
- 没有任何单一的测试证明了所有探索的非正常形式的稳定性.
- 性能因参数空间和分布假设而有所不同.
结论:
- 研究人员在选择统计测试来比较依赖相关性与重叠变量时应谨慎.
- 由于准确性不佳,不推评估的五项测试.
- 剩下的五个测试提供了可行的选择,但应该考虑它们的强度限制.
- 提供了实用建议,以帮助根据研究细节选择最合适的测试.
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