对子群的标准误差估计 非不变性估计
1ETS Research Institute, ETS, Princeton, NJ, USA.
Applied psychological measurement
|July 8, 2025
概括
新的方法通过将错误依赖关系考虑在内,准确地评估分数,将分群之间的公平性联系起来. 这样可以更好地检测标准化测试中的公平性问题.
科学领域:
- 心理测量 心理测量 心理测量
- 教育测量教育的测量
- 统计建模 统计建模
背景情况:
- 评分链接对于在不同尺度或条件下比较评估分数至关重要.
- 确保公平性要求连接功能在不同亚群体之间是不变的.
- 由于复杂的错误依赖,现有的方法难以准确评估子群差异.
研究的目的:
- 开发和验证新的统计方法来评估分数连接不变性跨子群体.
- 为了解决目前忽视链接错误依赖性的方法中标准错误的高估问题.
- 提高在教育和心理评估中检测公平违规行为的能力.
主要方法:
- 开发统计模型,明确纳入链接错误依赖关系.
- 模拟研究是为了在各种条件下评估拟议方法的准确性和性能.
- 将新方法应用于现实世界的数据集以进行实际验证.
主要成果:
- 拟议的方法提供了准确的标准误差估计,用于链接得分的分群差异.
- 忽视或误解链接错误依赖导致标准错误的高估.
- 新的方法显著增加了检测子群体间非不变的统计能力.
结论:
- 准确的对链接错误依赖性的核算对于在分数链接中有效的公平性评估至关重要.
- 开发的方法提供了一种更可靠的方法,以确保标准化测试中的公平性.
- 改进的标准错误估计有助于更有效地检测公平性问题,支持公平的评估实践.
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