认知诊断模型中项目水平模型比较统计量的健壮性  

The Robustness of the Item-Level Model Comparison Statistics in Cognitive Diagnostic Models

作　　者：刘彦楼 张倩萌 郑宗军[3] 尹昊 Liu Yanlou;Zhang Qianmeng;Zheng Zongjun;Yin Hao(China Academy of Big Data for Education,Qufu Normal University,Qufu,273165;School of Education,Qufu Normal University,Qufu,273165;Teacher Education College,Taishan University,Tai'an,271000)

机构地区：[1]曲阜师范大学中国教育大数据研究院,曲阜273165 [2]曲阜师范大学教育学院,曲阜273165 [3]泰山学院教师教育学院,泰安271000

出　　处：《心理科学》2019年第5期1251-1259,共9页Journal of Psychological Science

基　　金：山东省社会科学基金项目(18CJYJ16)的资助

摘　　要：采使用模拟研究方法比较了以往研究中提出的基于观察信息矩阵、三明治矩阵的Wald(分别表示为WObs、WSw)、似然比(Likelihood Ratio)统计量以及新提出的基于经验交叉相乘信息矩阵的Wald统计量(WXPD)在模型--数据失拟条件下进行项目水平上模型比较时的表现。结果显示:(1)WSw的一类错误控制率有很强的健壮性。(2)N>500时,WXPD在Q矩阵错误设定的大多数条件下的表现优于WSw。结论:模型--数据拟合良好时可以使用WSw进行项目水平上的模型比较,当模型与数据失拟时WXPD可能是更好的选择。For the past decade,cognitive diagnostic models(CDMs)have received considerable attention as a psychometric model.A variety of specific and general CDMs with different assumptions about how an examinee’s latent attribute mastery pattern influence test performance have been developed in the literature.For example,the deterministic inputs,noisy"and"gate model(DINA),the deterministic inputs,noisy"or"gate model(DINO),the additive cognitive diagnostic model(A-CDM)are specific CDMs.The log-linear cognitive diagnosis model,the generalized DINA model(G-DINA)and the general diagnostic model are example of general CDMs.Although specific CDMs can be shown as special cases of the general models,selecting the most appropriate CDM at the item level is of great important to researchers and practitioners,since the correctly specified CDM can provide higher accurate attribute mastery pattern estimates than a general CDM.Under the conditions that the Q-matrix is correctly specified and the saturated model provides the best model-data fit,many methods are available for selecting the most appropriate CDM from the saturated CDM at the item level,such as the Wald and likelihood ratio(LR)tests.However,CDM is a simplification of reality,under the most circumstance if not all,CDMs seldom perfectly represent real world phenomena.It is reasonable to explore the robustness of item level model comparison statistics under model-data misfit condition.The primary purpose of this simulation study was to investigate the impact of the model-data misfit on the empirical performance of the Wald statistic based on the observed information(WObs)or the sandwich-type matrix(WSw),the LR statistic,and a new proposed Wald statistic computation method that is the Wald statistic based on the empirical cross-product information matrix(WXPD)for item-level model selection with respect to the Type I error and power.Four factors were manipulated in the simulation:Four Sample Sizes×Three data generating models×Two Q-matrix Specification Types×Four item-level

关 键 词：认知诊断模型 信息矩阵 三明治矩阵 Wald统计量 模型比较 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]