在z-转换相关联的元分析中纠正测量误差
1Florida State University, Tallahassee, Florida, USA.
The British journal of mathematical and statistical psychology
|December 29, 2023
概括
本研究引入了新的方法来纠正相关性元分析中的测量错误. 建议稳定一级和二级校正,以提高估计平均相关性和同质性测试的准确性.
科学领域:
- 心理测量 心理测量 心理测量
- 统计方法 统计方法
- 进行元分析分析.
背景情况:
- 分析依赖于准确的相关性估计,但测量错误可以减弱真实关系.
- 在元分析中纠正测量误差的现有方法主要集中在原始相关性上,对校正相关性的研究内采样误差差异的关注较少.
研究的目的:
- 评估和比较不同的方法来纠正费舍尔的z转换相关性在计算测量误差后的研究内采样误差差异.
- 在估计平均相关性和同质性测试中评估这些修正变异的准确性.
主要方法:
- 采用斯皮尔曼的淡化公式来纠正测量错误的原始相关性.
- 研究了三种研究内部抽样错误差异估计器:线性校正,稳定第一阶段校正和稳定第二阶段校正.
- 进行了模拟研究,将这些估计器与未经纠正的差异估计器进行比较,使用系数alpha进行可靠性估计.
主要成果:
- 为了估计平均相关性,线性校正,稳定第一阶段和第二阶段的校正,以及没有进行的校正.
- 对于同质性测试,稳定一级和二级校正表明更好地控制了I型错误率,特别是在大样本大小和正常真分数的情况下.
结论:
- 在估计平均相关性和测试均性时,建议在元分析中使用稳定的一级和二级校正,特别是在正常的真分数,可接受的可靠性和大样本大小的情况下.
- 这些先进的校正方法在元分析研究中提高了统计推理的准确性.
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