Xiaofeng YOU

Biographic Data

ID8916984
NAMEXiaofeng YOU
GIVEN NAMESXiaofeng
FAMILY NAMEYOU
SIGNATUREYOU X
AFFILIATIONSBeijing Normal University
VERIFIEDNo
TOTAL WORKS4
TOTAL CITATIONS0
AUTHOR COUNT4
EDITOR COUNT0
FIRST PUBLICATION YEAR2010
LATEST PUBLICATION YEAR2024
H-INDEX0

  • Confidence interval width contours

    Yue Liu, Lei Xu et al.ARTICLEActa Psychologica Sinica2024

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  • Missing data analysis in cognitive diagnostic models

    Xiaofeng YOU, Jianqin YANG et al.ARTICLEActa Psychologica Sinica2023

    摘要: 认知诊断测评中缺失数据的处理是理论和实际应用者非常关注的研究主题。借鉴随机森林插补法(RFI)不依赖于缺失机制假设的特点, 对已有的RFI方法进行改进, 提出采用个人拟合指标(RCI)确定插补阈值的新方法: 随机森林阈值插补方法(RFTI)。模拟研究表明, RFTI在插补正确率上明显高于RFI方法; 与RFI和EM方法相比, RFTI在被试属性模式判准率和边际判准率上表现出明显优势, 尤其是非随机缺失和混合缺失机制, 以及缺失比例较高的条件下, 其优势更加明显。但对项目参数的估计, RFTI方法与EM方法相比不具有优势

  • A comparison of standard residual methods and a mixture hierarchical model for detecting non-effortful responses

    Yue Liu, Hongyun Liu et al.ARTICLEActa Psychologica Sinica2022

    Assessment datasets contaminated by non-effortful responses may lead to serious consequences if not handled appropriately. Previous research has proposed two different strategies: down-weighting and accommodating. Down-weighting tries to limit the influence of aberrant responses on parameter estimation by reducing their weight. The extreme form of down-weighting is the detection and removal of irregular responses and response times (RTs). The sta…

  • Parameter Estimation of the Raw Item in Computerized Adaptive Testing

    Xiaofeng YOU, Xiao-Feng YOU et al.ARTICLEActa Psychologica Sinica2010

    摘要: 计算机化自适应测验(Computerized Adaptive Testing, 简称CAT)其安全性面临着新的挑战, 小题库的安全更受威胁。如何建设一个大型、优质的题库成为CAT研究中一个非常重要的课题。目前CAT题库的建设存在一些问题, 如成本高且保密性较差。尤其是等值技术较复杂且锚题重复使用容易造成泄露。如能在实施CAT过程中插入未经过参数估计的项目(原始题), 同时对原始题项目参数进行估计, 这对建设大型、优质的CAT题库来说其意义是不言而喻的。本文基于1PLM和2PLM对此进行研究, 提出了原始题在线估计的新方法以及推导出了求区分度参数a迭代初值的计算公式。研究结果表明:无论是模拟研究还是实证研究, 原始题被作答的次数对项目参数估计结果都会产生不同的影响, 并且原始题作答人数越多项目参数估计精度也越高