我们的网站为什么显示成这样?

可能因为您的浏览器不支持样式,您可以更新您的浏览器到最新版本,以获取对此功能的支持,访问下面的网站,获取关于浏览器的信息:

|本期目录/Table of Contents|

 方差—协方差矩阵在认知诊断中的作用(PDF)

《心理学探新》[ISSN:1003-5184/CN:36-1228/B]

期数:
 2023年03期
页码:
 262-268
栏目:
 心理统计与测量
出版日期:
 2023-07-20

文章信息/Info

Title:
 The Variance-covariance Matrix based Statistical Inferences in Cognitive Diagnostic Models
文章编号:
1003-5184(2023)03-0262-07
作者:
 吴琼琼1赵 悦1刘彦楼2
 (1.曲阜师范大学心理学院,济宁 273165; 2.曲阜师范大学教育大数据研究院,济宁 273165)
Author(s):
 Wu Qiongqiong1Zhao Yue1Liu Yanlou2
 (1.School of Psychology,Qufu Normal University,Jining 273165; 2.Academy of Big Data for Education,Qufu Normal University,Jining 273165)
关键词:
 认知诊断模型 方差—协方差矩阵 信息矩阵 标准误 Q矩阵修正
Keywords:
 cognitive diagnosis models variance-covariance matrix information matrix standard error the Q-matrix validation
分类号:
 B841.2
DOI:
 -
文献标识码:
 A
摘要:
 认知诊断模型(cognitive diagnostic model,CDM)的统计检验目前主要包括模型参数的标准误估计、项目功能差异检验、项目水平模型比较、Q矩阵修正、属性层级关系探索等5个重要的研究领域。方差—协方差矩阵(信息矩阵的逆矩阵)在CDM的以上5种统计检验中具有基础和核心的作用。文章评述了方差—协方差矩阵在CDM的统计检验中的作用,梳理了以往研究者提出的信息矩阵估计方法的发展思路和脉络。最后对已有研究存在的重要问题进行讨论和展望。
Abstract:
 The variance-covariance matrix for the maximum likelihood estimates of model parameters in cognitive diagnostic models plays a key role in statistical inference.We(a)extensively analyze the applications of variance-covariance matrixin various fields of cognitive diagnosis,including the estimation of models parameter standard error,detection of differential item functioning,item-level comparison of saturated and reduced models,the Q-matrix estimation or validation and attribute hierarchy exploration,(b)provide possible explanations forprevious study resultsand suggests how to advance the application of variance-covariance matrix,(c)introduce 13 information matrix estimation methods proposed in literature,which are classified according to whether structural parameters are considered,(d)briefly comment the advantages or disadvantages of these methods.We conclude by discussing future directions for variance-covariance matrix research.

参考文献/References

 高一珠,陈孚,辛涛,詹沛达,姜宇.(2017).心理测量学模型在学习进阶中的应用:理论、途径和突破.心理科学进展,25(9),1623-1630.
姜宇.(2020).基于信息矩阵的属性层级关系检验方法研究(博士学位论文).北京师范大学,北京.
刘彦楼.(2022).认知诊断模型的标准误与置信区间估计:并行自助法.心理学报,54(6),1-22.
刘彦楼,辛涛,李令青,田伟,刘笑笑.(2016).改进的认知诊断模型项目功能差异检验方法——基于观察信息矩阵的Wald统计量.心理学报,48(5),588-598.
刘彦楼,张倩萌,郑宗军,尹昊.(2019).认知诊断模型中项目水平模型比较统计量的健壮性.心理科学,42(5),1251-1259.
涂冬波,蔡艳,戴海琦,丁树良.(2010).一种多级评分的认知诊断模型:P-DINA模型的开发.心理学报,42(10),1011-1020.
魏丹,张丹慧,刘红云.(2020).基于多维题组反应模型的项目功能差异检验探究.心理科学,43(1),206-214.
汪大勋,高旭亮,蔡艳,涂冬波.(2020).基于类别水平的多级计分认知诊断Q矩阵修正:相对拟合统计量视角.心理学报,52(1),93-106.
汪文义,朱黎君,叶宝娟,方小婷.(2020).Bootstrap 区间估计在认知诊断模型误设中的应用.心理科学,43(6),1498-1505.
王卓然,郭磊,边玉芳.(2014).认知诊断测验中的项目功能差异检测方法比较.心理学报,46(12),1923-1932.
Cai,L.(2008).SEM of another flavour:Two new applications of the supplemented EM algorithm.British Journal of Mathematical and Statistical Psychology,61(2),309-329.
Chalmers,R.P.(2018).Numerical approximation of the observed information matrix with Oakes' identity.British Journal of Mathematical and Statistical Psychology,71(3),415-436.
Chiu,C.-Y.(2013).Statistical refinement of the Q-matrix in cognitive diagnosis.Applied Psychological Measurement,37(8),598-618.
de la Torre,J.(2009).DINA model and parameter estimation:A didactic.Journal of Educational and Behavioral Statistics,34(1),115-130.
de la Torre,J.(2011).The generalized DINA model framework.Psychometrika,76(2),179-199.
de la Torre,J.,& Chiu,C.-Y.(2016).A general method of empirical Q-matrix validation.Psychometrika,81(2),253-273.
de la Torre,J.,& Lee,Y.S.(2013).Evaluating the Wald test for item-level comparison of saturated and reduced models in cognitive diagnosis. Journal of Educational Measurement,50(4),355-373.
DeCarlo,T.(2019).Insights from reparameterized DINA and beyond.In M.von Davier & Y.-S.Lee(Eds.),Handbook of diagnostic classification models(pp.549-572).Springer.
George,A.C.,Robitzsch,A.,Kiefer,T.,Gross,J.,& Uenlue,A.(2016).The R package CDM for cognitive diagnosis models. Journal of Statistical Software,74(2),1-24.
Hou,L.,de la Torre,J.,& Nandakumar,R.(2014).Differential item functioning assessment in cognitive diagnostic modeling:Application of the Wald test to investigate DIF in the DINA model.Journal of Educational Measurement,51(1),98-125.
Hou,L.,Terzi,R.,& de la Torre,J.(2020).Wald test formulations in DIF detection of CDM data with the proportional reasoning test.International Journal of Assessment Tools in Education,7(2),145-158.
Leighton,J.P.,Gierl,M.J.,& Hunka,S.M.(2004).The attribute hierarchy method for cognitive assessment:A variation on Tatsuoka's rule-space approach. Journal of Educational Measurement,41(3),205-237.
Liu,Y.,Andersson,B.,Xin,T.,Zhang,H.,& Wang,L.(2019).Improved Wald statistics for item-level model comparison in diagnostic classification models.Applied Psychological Measurement,43(5),402-414.
Liu,Y.,Tian,W.,& Xin,T.(2016).An application of M2 statistic to evaluate the fit of cognitive diagnostic models.Journal of Educational and Behavioral Statistics,41(1),3-26.
Liu,Y.,& Xin,T.(2017).Dcminfo:Information matrix for diagnostic classification models.R package version 0.1.6.https://CRAN.R-project.org/package=dcminfo
Liu,Y.,Xin,T.,Andersson,B.,& Tian,W.(2019).Information matrix estimation procedures for cognitive diagnostic models.British Journal of Mathematical and Statistical Psychology,72(1),18-37.
Liu,Y.,Xin,T.,& Jiang,Y.(2021).Structural parameter standard error estimation method in diagnostic classification models:Estimation and application.Multivariate Behavioral Research,57(5),784-803.
Liu,Y.,Yin,H.,Xin,T.,Shao,L.,& Yuan,L.(2019).A comparison of differential item functioning detection methods in cognitive diagnostic models.Frontiers in Psychology,10,1137.
Ma,W.,& de la Torre,J.(2016).A sequential cognitive diagnosis model for polytomous responses.British Journal of Mathematical and Statistical Psychology,69(3),253-275.
Ma,W.,& de la Torre,J.(2019).Category-level model selection for the sequential G-DINA model.Journal of Educational and Behavioral Statistics,44(1),45-77.
Ma,W.,& de la Torre,J.(2020a).An empirical Q‐matrix validation method for the sequential generalized DINA model.British Journal of Mathematical and Statistical Psychology,73(1),142-163.
Ma,W.,& de laTorre,J.(2020b).GDINA:An R package for cognitive diagnosis modeling.Journal of Statistical Software,93(14),1-26.
Ma,W.,Ragip,T.,& de la Torre,J.(2021).Detecting differential item functioning using multiple-group cognitive diagnosis models.Applied Psychological Measurement,45(1),37-53.
Philipp,M.,Strobl,C.,de la Torre,J.,& Zeileis,A.(2018).On the Estimation of Standard Errors in Cognitive Diagnosis Models.Journal of Educational and Behavioral Statistics,43(1),88-115.
Robitzsch,A.,& George,A.C.(2019).The R package CDM.In M.von Davier & Y.-S.Lee(Eds.),Handbook of diagnostic classification models(pp.549-572).Springer.https://doi.org/ 10.1007/9783-030055844_26
Sorrel,M.A.,Olea,J.,Abad,F.J.,de la Torre,J.,Aguado,D.,& Lievens,F.(2016).Validity and reliability of situational judgment test scores:A new approach based on cognitive diagnosis models.Organizational Research Methods,19,506-532.
Templin,J.,& Bradshaw,L.(2014).Hierarchical diagnostic classification models:A family of models for estimating and testing attribute hierarchies.Psychometrika,79(2),317-339.
Tian,W.,Cai,L.,Thissen,D.,& Xin,T.(2013).Numerical differentiation methods for computing error covariance matrices in item response theory modeling:An evaluation and a new proposal.Educational and Psychological Measurement,73(3),412-439.
von Davier,M.,& Haberman,S.J.(2014).Hierarchical diagnostic classification models morphing into unidimensional ‘diagnostic' classification models—a commentary.Psychometrika,79(2),340-346.
Wainer,H.,& Wright,B.D.(1980).Robust estimation of ability in the Rasch model.Psychometrika,45(3),373-391.

备注/Memo

备注/Memo:
 通讯作者:刘彦楼,E-mail:liuyanlou@163.com。
更新日期/Last Update:  2023-10-20