一种非参数化的Q矩阵估计方法：ICC-IR方法开发

摘要：相对于参数化的方法,本研究根据题目测量模式关系开发出ICC指标,并提出基于理想得分的ICC指标法进行Q矩阵估计。Monte Carlo模拟研究与实证研究发现（1）基于理想得分ICC指标法估计Q矩阵具有很好的效果,当属性个数越少、基础题个数越多,估计效果越好。（2）相对于以往方法——D2统计量的方法,ICC-IR法效果更好,并且是一种非参数化的方法,计算简单快捷。（3）实证数据分析表明,ICC-IR法估计的Q矩阵在模型拟合度上也优于D2统计量方法。     

Cognitive diagnosis modelling incorporating item response times

To provide more refined diagnostic feedback with collateral information in item response times (RTs), this study proposed joint modelling of attributes and response speed using item responses and RTs simultaneously for cognitive diagnosis. For illustration, an extended deterministic input, noisy ‘and’ gate (DINA) model was proposed for joint modelling of responses and RTs. Model parameter estimation was explored using the Bayesian Markov chain Monte Carlo (MCMC) method. The PISA 2012 computer-based mathematics data were analysed first. These real data estimates were treated as true values in a subsequent simulation study. A follow-up simulation study with ideal testing conditions was conducted as well to further evaluate model parameter recovery. The results indicated that model parameters could be well recovered using the MCMC approach. Further, incorporating RTs into the DINA model would improve attribute and profile correct classification rates and result in more accurate and precise estimation of the model parameters.     

Two-Stage maximum likelihood estimation in the misspecified restricted latent class model

The maximum likelihood classification rule is a standard method to classify examinee attribute profiles in cognitive diagnosis models (CDMs). Its asymptotic behaviour is well understood when the model is assumed to be correct, but has not been explored in the case of misspecified latent class models. This paper investigates the asymptotic behaviour of a two-stage maximum likelihood classifier under a misspecified CDM. The analysis is conducted in a general restricted latent class model framework addressing all types of CDMs. Sufficient conditions are proposed under which a consistent classification can be obtained by using a misspecified model. Discussions are also provided on the inconsistency of classification under certain model misspecification scenarios. Simulation studies and a real data application are conducted to illustrate these results. Our findings can provide some guidelines as to when a misspecified simple model or a general model can be used to provide a good classification result.     

A general proof of consistency of heuristic classification for cognitive diagnosis models

The Asymptotic Classification Theory of Cognitive Diagnosis (Chiu et al., 2009, Psychometrika, 74, 633–665) determined the conditions that cognitive diagnosis models must satisfy so that the correct assignment of examinees to proficiency classes is guaranteed when non‐parametric classification methods are used. These conditions have only been proven for the Deterministic Input Noisy Output AND gate model. For other cognitive diagnosis models, no theoretical legitimization exists for using non‐parametric classification techniques for assigning examinees to proficiency classes. The specific statistical properties of different cognitive diagnosis models require tailored proofs of the conditions of the Asymptotic Classification Theory of Cognitive Diagnosis for each individual model – a tedious undertaking in light of the numerous models presented in the literature. In this paper a different way is presented to address this task. The unified mathematical framework of general cognitive diagnosis models is used as a theoretical basis for a general proof that under mild regularity conditions any cognitive diagnosis model is covered by the Asymptotic Classification Theory of Cognitive Diagnosis.     

要注意中药对肝的损伤作用

含有生物碱类、皂苷类、萜类、毒蛋白类、重金属类成分的中药易致急性肝损伤.中药对肝脏损伤的原因及机制较为复杂,可能与药物对肝脏的直接毒性或特异性体质有关.此外,中药炮制方法、给药途径、剂型、剂量、疗程及配伍不当也会引起药物性肝损伤.中药所致的药物性肝损伤的诊断主要依据用药史、发病的时间、过程和临床表现并排除其他因素.治疗可选用还原型谷胱甘肽、S-腺苷蛋氨酸、多烯磷脂酰胆碱、熊去氧胆酸、水飞蓟素等药物,重症可选择人工肝脏支持治疗.     

阿尔茨海默病生物学标志物研究进展

阿尔茨海默病（AD）是常见的中枢神经系统变性疾病,是痴呆最常见的病因,发病率高.病理特征为老年斑及神经元纤维缠结.AD的确诊有赖病理学,临床诊断极其耗时.由于尚无准确的早期诊断方法,常使AD患者错过早期治疗的时机,这成为制约有效防控AD的瓶颈问题.因此寻找高敏感性、特异性、无创性的生物学标志物对AD的早期诊断至关重要.本文仅将目前较为广泛研究的生物学标志物及其研究现状作一概述.分别对脑脊液、血液、尿液及唾液中的AD标志物作逐一介绍.     

妊娠合并结核临床诊治的决策

妊娠合并结核是一种对母婴健康危害极大的妊娠期疾病。在妊娠期结核病中,多数患者无明显症状,早期症状与妊娠期某些生理反应相似,加之妊娠与结核病的相互影响,x线、CT等重要的影像学检查受限,致使本病易被误诊或误治。某些抗结核药物对母婴的不良影响,使其治疗难以实施,由于结核病本身及治疗后可能对胎儿的影响,在临床上是否终止妊娠往往难以决策。本文就妊娠合并结核诊治过程中的相关问题进行综述,以期为临床诊治决策提供帮助。     

心力衰竭国内外指南浅析

近几年随着循证医学证据的不断增加,各国对心力衰竭指南进行了更新.主要是2012年欧洲心脏病学会(ESC)与心衰学会公布的心力衰竭新指南、2011年澳大利亚和新西兰慢性心力衰竭诊治指南、2010年英国国立健康与临床优化研究所(NICE)慢性心力衰竭诊治指南、2009美国心脏病学会(ACC)/美国心脏协会(AHA)实践指南工作组成人心力衰竭诊疗指南及2010年我国的急性心力衰竭指南等.各国指南对心力衰竭的诊断和治疗都提出了具体的意见和建议,其中不乏亮点,如对慢性心力衰竭患者更加重视血运重建的治疗作用、推荐心力衰竭治疗的一种新型β受体阻滞剂奈必洛尔等等.我们对以上几个指南做了浅要分析,以取长补短更规范的诊治心力衰竭患者.     

一种多级评分的广义认知诊断模型

认知诊断是近些年教育测量研究中的热点,大多数的认知诊断模型仅适用于0～1评分的情况.本文提出一种有多个潜变量多个滑动参数的多级评分认知诊断模型——GP-D1NA,只要由评分标准和知识状态能确定理想反应模式,就可以利用此方法进行认知诊断分析.在该方法中,我们给出项目滑动矩阵的概念,将被试的观测得分均看成由某个理想得分的滑动,并采用EM算法估计滑动矩阵.在模拟研究中,采用每掌握一个属性得1分的评分标准,结果表明线性型、收敛型、发散型、无结构型和独立型五种属性层级结构均有较高的判准率.     

认知诊断分类中心的确定

期望反应模式是认知诊断分类的类中心,确定了诊断范围中属性及其层级关系后,类中心的数目由测验Q矩阵决定.类中心应该是完备的,即理论上有多少个知识状态就应该有多少个类中心,这涉及评分方式、Q矩阵设计、Q矩阵评价与修改、认知诊断测验如何实施等问题的讨论.重点给出多级评分认知诊断测验不同属性层级对应的完备Q矩阵设计的例子和罗列了Wang等人（2013）的Q矩阵修改的方法.