ISSN 1671-3710
CN 11-4766/R
主办：中国科学院心理研究所
出版：科学出版社

心理科学进展 ›› 2014, Vol. 22 ›› Issue (8): 1350-1362.doi: 10.3724/SP.J.1042.2014.01350

• 研究方法 • 上一篇    

项目反应理论中模型-资料拟合检验常用统计量

单昕彤;谭辉晔;刘永;吴方文;涂冬波   

  1. (江西师范大学心理学院, 南昌 330027)
  • 收稿日期:2013-12-07 出版日期:2014-08-15 发布日期:2014-08-15
  • 通讯作者: 涂冬波
  • 基金资助:

    国家自然科学基金(31100756, 31300876, 31360237, 31160203), 教育部人文社科项目(11YJC190002), 江西省社科规划重点项目(13JY01), 高等院校博士点基金项目(编号：20123604120001), 江西教育科学规划 (12YB088, 13YB029), 江西省教育厅科技计划项目(编号: GJJ13266)和江西师范大学青年英才培育资助计划等资肋。

Common Model-Data Fit Test Statistics in Item Response Theory

SHAN Xintong;TAN Huiye;LIU Yong;WU Fangwen;TU Dongbo   

  1. (College of Psychology, Jiangxi Normal University, Nanchang 330022, China)
  • Received:2013-12-07 Online:2014-08-15 Published:2014-08-15
  • Contact: TU Dongbo

PDF (PC)

2267

被引次数

7

摘要：

项目反应理论(IRT)模型依据项目与被试的特征预测被试的作答表现, 是常用的心理测量模型。但IRT的有效运用依赖于所选用IRT模型与实际数据资料相符合的程度(即模型?资料拟合度, goodness of fit)。只有当所采用IRT分析模型与实际数据资料拟合较好时, IRT的优点和功能才能真正发挥出来(Orlando & Thissen, 2000)。而当所采用IRT模型与资料不拟合或选择了错误的模型, 则会导致如参数估计、测验等值及项目功能差异分析等具有较大误差(Kang, Cohen & Sung, 2009), 给实际工作带来不良影响。因此, 在使用IRT分析时, 应首先充分考察及检验所选用模型与实际数据是否相匹配/相拟合(McKinley & Mills, 1985)。IRT领域中常用模型?资料拟合检验统计量可从项目拟合、测验拟合两个角度进行阐述并比较, 这是心理、教育测量领域的重要主题, 也是测验分析过程中较易忽视的环节, 目前还未见此类公开发表的文章。未来的研究可以在各统计量的实证比较研究以及在认知诊断领域的拓展方面有所发展。

关键词: 项目反应理论, 模型-资料拟合检验, 项目拟合, 测验拟合

Abstract:

Item response theory (IRT) models are widely applied psychometric models. They can predict responses based on characteristics of items and participants. But the validity in all applications of IRT is dependent on the extent to which the selected model accurately reflects the data at hand (goodness of fit). Only when the IRT model fits the data well, can the advantages and functions of IRT emerge (Orlando & Thissen, 2000). Selection of the wrong model would lead to relatively large error in parameter estimation, test equating, the analysis of differential item functioning and so on, which would result in adverse effect (Kang, Cohen & Sung, 2009). Therefore, it is required to evaluate model-data fit before applying IRT (McKinley & Mills, 1985). Common fit statistics in the field of IRT can be expounded and compared from test fit and item fit, which is very important in the field of psychological and educational measurement and also easily neglected in test analysis process. It has not been found yet that there are any similar published articles. Directions of future research for model-data fit could emphasize simulation and empirical study of this issue. And common fit statistics in the field of cognitive diagnosis could be investigated.

Key words: Item Response Theory, Test of Model-Data Fit, Item Fit, Test Fit