基于贝叶斯网模型的多级计分诊断测验分类及比较研究

贝叶斯网模型提供了一种方便和直观的框架结构来表示变量间的关系,非常适合在诊断测验中对教育评估的内容进行建模。本研究将两种贝叶斯网分类模型与序列多级计分诊断模型S-GDINA进行综合比较。考察两种贝叶斯网分类模型与S-GDINA在Q矩阵正确界定和包含一定比例(25%、 30%)的错误时,两者对被试的分类性能;并将贝叶斯网分类模型应用到实证数据中,展示贝叶斯网分类模型在实证数据中的分类过程和分类性能。研究结果表明：当Q矩阵由专家正确界定时,朴素贝叶斯分类模型的分类效果与S-GDINA模型相差不大,同样可以达到很好的分类效果,树增广的朴素贝叶斯分类模型的分类性能也能达到良好。实证结果进一步表明,将贝叶斯网分类模型应用于教育测量领域中的诊断分类工具是有其优势和可行的,尤其是当测验数据对于所选用诊断模型的拟合较差、测验的Q矩阵中包含错误或测验数据中包含较多的噪音时。     

Abstract: A Comparison of the Factor Mixture Model and Taxometric Procedures

Taxometric procedures and the Factor Mixture Model (FMM) have a complimentary set of strengths and weaknesses. Both approaches purport to detect evidence of a latent class structure. Taxometric procedures, popular in psychiatric and psychopathology literature, make no assumptions beyond those needed to compute means and covariances. However, Taxometric procedures assume that observed items are uncorrelated within a class or taxon. This assumption is violated when there are individual differences in the trait underlying the items (i.e., severity differences within class). FMMs can model within-class covariance structures ranging from local independence to multidimensional within-class factor models and permits the specification of more than two classes. FMMs typically rely on normality assumptions for within-class factors and error terms. FMMs are highly parameterized and susceptible to misspecifications of the within-class covariance structure.

The current study compared the Taxometric procedures MAXEIG and the Base-Rate Classification Technique to the FMM in their respective abilities to (1) correctly detect the two-class structure in simulated data, and to (2) correctly assign subjects to classes. Two class data were simulated under conditions of balanced and imbalanced relative class size, high and low class separation, and 1-factor and 2-factor within-class covariance structures. For the 2-factor data, simple and cross-loaded factor loading structures, and positive and negative factor correlations were considered. For the FMM, both correct and incorrect within-class factor structures were fit to the data.

FMMs generally outperformed Taxometric procedures in terms of both class detection and in assigning subjects to classes. Imbalanced relative class size (e.g., a small minority class and a large majority class) negatively impacted both FMM and Taxometric performance while low class separation was much more problematic for Taxometric procedures than the FMM. Comparisons of alterative FMMs based on information criteria generally resulted in correct model choice but deteriorated when small class separation was combined with imbalanced relative class size.     

Skills Training for Spouses of Patients with Alzheimer's Disease: Outcomes of an Intervention Study

The effects of a 12-week intervention on a patient-focused skills training group and a caregiver-focused skills training group were compared with those on a control group that received comparable attention, but no training. Intervention effects were monitored at the completion of the treatment phase and at 3- and 6-months postintervention. Treatment implementation was documented in a comprehensive fashion to ensure replicability. Both training groups acquired skills that enabled them to improve targeted behaviors (patient problem behaviors and caregiver mood, respectively). Weaker effects were found for more distal outcomes, such as depression, perceived stress, caregiver strain, and self-efficacy.     

非参数认知诊断方法下诊断结果的概率化表征

非参数认知诊断分类方法非常适合课堂评估,其诊断结果采用0-1形式而缺乏概率化表征,不能精细地区分被试属性掌握程度的差异或变化,还缺乏可用于评价真实测验分类结果的信度和效度指标。要刻画被试属性掌握程度的差异,首要的问题是要为非参数认知诊断方法提供一种可以量化属性掌握概率的方法。针对此问题,基于二项分布和玻尔兹曼分布提出非参数认知诊断方法下诊断结果的概率化表征方法,并用于构建分类准确性和分类一致性指标。模拟研究与实测数据分析结果显示：概率化表征方法与非参数认知诊断方法的分类结果高度一致;概率化表征方法与认知诊断模型所得的属性掌握概率十分接近;概率化表征方法所得的属性（模式）掌握概率可用于计算属性（模式）分类准确性和分类一致性指标,在实际测验情景下可作为信度和效度指标,评价诊断结果的重测一致率和判准率。     

Emerging therapeutics for Alzheimer's disease: an avenue of hope

Emerging therapies for Alzheimer's disease offer hope to patients and their caregivers. Future treatments will probably include combination approaches with agents that modify amyloid processing, deposition, and clearance. One example, the AD vaccine, reduced amyloid burden and changed behavior in animal models of AD, but the human trial was halted when several subjects developed brain inflammation. Anti-inflammatory agents have epidemiologic support, but clinical trials have been disappointing, possibly related to inadequate study with anti-inflammatory agents that modify amyloid processing. Agents that target known cardiovascular risk factors, such as hypercholesterolemia, hypertension, and insulin resistance, have epidemiologic, preclinical, and clinical evidence to warrant further investigation. Heavy metal chelators, antioxidants, neurotrophic factors, glutaminergic modulators, and agents that modify hyperphosphorylation of Tau are other approaches in research and development.     

多种记忆分类之研究

1 引言 20世纪50年代初,人们便开始用信息加工理论的观点解释记忆现象,把记忆看成是信息编码、储存和提取的过程。从那以后,对记忆的分类也更多地基于记忆中的信息及其编码、储存、提取的不同。根据记忆信息储存时间的长短将记忆分为长时记忆、短时记忆、感觉记忆,根据记忆信息是语义还是情景的将记忆分为语义和情景记忆,根据根据记忆     

结直肠癌诊断技术述评

结直肠癌是消化道最常见的恶性肿瘤之一。目前结直肠癌诊断技术的研究涵盖了分子生物学、肿瘤学、影像学等多个学科,得到不断发展。在以往的诊断技术的基础上,结合新的理论和方法,采用正确的诊断策略及早发现结直肠癌对控制其发病率和病死率起着重要作用。     

Cognitive Diagnosis for Small Educational Programs: The General Nonparametric Classification Method

The focus of cognitive diagnosis (CD) is on evaluating an examinee’s strengths and weaknesses in terms of cognitive skills learned and skills that need study. Current methods for fitting CD models (CDMs) work well for large-scale assessments, where the data of hundreds or thousands of examinees are available. However, the development of CD-based assessment tools that can be used in small-scale test settings, say, for monitoring the instruction and learning process at the classroom level has not kept up with the rapid pace at which research and development proceeded for large-scale assessments. The main reason is that the sample sizes of the small-scale test settings are simply too small to guarantee the reliable estimation of item parameters and examinees’ proficiency class membership. In this article, a general nonparametric classification (GNPC) method that allows for assigning examinees to the correct proficiency classes with a high rate when sample sizes are at the classroom level is proposed as an extension of the nonparametric classification (NPC) method (Chiu and Douglas in J Classif 30:225–250, 2013). The proposed method remedies the shortcomings of the NPC method and can accommodate any CDM. The theoretical justification and the empirical studies are presented based on the saturated general CDMs, supporting the legitimacy of using the GNPC method with any CDM. The results from the simulation studies and real data analysis show that the GNPC method outperforms the general CDMs when samples are small.     

结直肠癌诊断技术述评

结直肠癌是消化道最常见的恶性肿瘤之一.目前结直肠癌诊断技术的研究涵盖了分子生物学、肿瘤学、影像学等多个学科,得到不断发展.在以往的诊断技术的基础上,结合新的理论和方法,采用正确的诊断策略及早发现结直肠癌对控制其发病率和病死率起着重要作用.     

Serum calcium levels in Alzheimer's disease: A finding and an aetiological hypothesis

We report that lower serum Ca²⁺ levels are found in severely demented patients when compared with mildly affected individuals (P < 0.001) and we formulate an aetiological hypothesis of Alzheimer's disease based on the disruption of intraneuronal microtubular networks by low calcium levels and other forms of intraneuronal mechanical disruption. The findings are discussed in relation to Hendrickson's theory of the biological basis of psychometric intelligence.     

Diagnosis of Personality Disorders: A Case Study

In this article, I report a case highlighting diagnostic uncertainty about psychopathology on both Axes I and II. It concerns in part the problem of comorbidity in relation to diagnostic classification of Axis II personality disorders. After commenting on these uncertainties in relation to categorical and dimensional models, I also consider a psychoanalytic explanation to illustrate an example in which a theoretical model informs diagnostic interviewing. I emphasize how the clinical information that unfolds from an interview based on this theoretical model generates inferences about psychopathology that extend clinical understanding beyond the formal diagnostic assessment of Axes I and II disorders and assessment by self-report.