评估不同级别的形状差异等同方法
1University of Utah, Salt Lake City, USA.
Educational and psychological measurement
|May 17, 2024
概括
选择正确的统计等同方法取决于不同测试形式的困难程度. 这项研究指导了从业人员选择适当的等分技术,以准确解释分数.
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:
- 为测试形式的难度差异进行等级调整,以确保可比得分.
- 当前的等式化实践往往忽视了形式难度变化的程度.
- 缺乏指导,以选择基于形式难度差异的等式化方法.
研究的目的:
- 调查不同形式的难度差异对等准确度的影响.
- 在不同的难度场景下,比较不同等级方法在不同难度场景下的性能.
- 提供以证据为基础的建议,用于等价方法的选择.
主要方法:
- 模拟研究评估六种等价方法.
- 研究了两种常见的等同设计:随机组 (RG) 和常见项目无等价组 (CINEG).
- 条件包括不同级别的形式难度差异,从没有到很大.
主要成果:
- 在RG设计中,平均等值在没有/小差异的情况下表现出色;对中等/大差异而言,平均等值优越.
- 对于CINEG设计,Tucker Linear在小/中差异方面表现最好;链式等比值或频率估计在大差异方面是最佳的.
- 方程式方法的性能受到形式难度差异的大小的显著影响.
结论:
- 这项研究为根据形式难度选择合适的等分方法提供了关键指导.
- 结果为测试公司提供了相似和不相似的测试形式的最佳等同策略的信息.
- 准确的得分可比性依赖于将等分方法与形式难度差异的程度相匹配.
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