• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of applied measurement >Detecting Rater Effects under Rating Designs with Varying Levels of Missingness
【24h】

Detecting Rater Effects under Rating Designs with Varying Levels of Missingness

机译：在缺失水平不同的评分设计下检测评分者影响

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Previous research has shown that indices obtained from partial credit model (PCM) estimates can detect severity and centrality rater effects, though it remains unknown how rater effect detection is impacted by the missingness inherent in double-scoring rating designs. This simulation study evaluated the impact of missing data on rater severity and centrality detection. Data were generated for each rater effect type, which varied in rater pool quality, rater effect prevalence and magnitude, and extent of missingness. Raters were flagged using rater location as a severity indicator and the standard deviation of rater thresholds a centrality indicator. Two methods of identifying extreme scores on these indices were compared. Results indicate that both methods result in low Type I and Type II error rates (i.e., incorrectly flagging non-effect raters and not flagging effect raters) and that the presence of missing data has negligible impact on the detection of severe and central raters.
机译：先前的研究表明，从部分信用模型（PCM）估计中获得的指数可以检测严重性和集中性评估者效应，尽管尚不清楚评估者效应检测如何受到双重得分评估设计固有的缺失的影响。该模拟研究评估了缺失数据对评估者严重性和集中性检测的影响。为每种评估者效应类型生成了数据，这些数据在评估者库质量，评估者效应患病率和严重性以及缺失程度方面有所不同。使用评估者的位置作为严重性指标，对评估者进行标记，评估者阈值的标准偏差作为中心度指标。比较了在这些指数上确定极端得分的两种方法。结果表明，这两种方法均导致I型和II型错误率较低（即错误地标记了无效评估者而不是标记效应评估者），并且缺少数据对严重和集中评估者的检测影响可忽略不计。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号