Nonparametric Calibration of Item-by-Attribute Matrix in Cognitive Diagnosis

A nonparametric technique based on the Hamming distance is proposed in this research by recognizing that once the attribute vector is known, or correctly estimated with high probability, one can determine the item-by-attribute vectors for new items undergoing calibration. We consider the setting where Q is known for a large item bank, and the q-vectors of additional items are estimated. The method is studied in simulation under a wide variety of conditions, and is illustrated with the Tatsuoka fraction subtraction data. A consistency theorem is developed giving conditions under which nonparametric Q calibration can be expected to work.     

Judging the animacy of words: The influence of typicality and age of acquisition in a semantic decision task

The age at which members of a semantic category are learned (age of acquisition), the typicality they demonstrate within their corresponding category, and the semantic domain to which they belong (living, non-living) are known to influence the speed and accuracy of lexical/semantic processing. So far, only a few studies have looked at the origin of age of acquisition and its interdependence with typicality and semantic domain within the same experimental design. Twenty adult participants performed an animacy decision task in which nouns were classified according to their semantic domain as being living or non-living. Response times were influenced by the independent main effects of each parameter: typicality, age of acquisition, semantic domain, and frequency. However, there were no interactions. The results are discussed with respect to recent models concerning the origin of age of acquisition effects.     

青少年分类能力发展特点的眼动研究

在目标匹配范式下,使用表示现实生活中的物体和场景关系的手绘黑白图片材料,通过眼动记录法考察了136名中学生和大学生分类加工过程的发展特点。结果表明,青少年分类能力发展存在显著的年级效应。不论是从分类结果还是从分类加工过程中看,青少年分类概括的能力并没有进入了平稳发展的阶段而是随着年级的升高而增长。高中阶段为分类能力发展的过渡阶段。     

aPRIDIT Unsupervised Classification with Asymmetric Valuation of Variable Discriminatory Worth

Abstract

Sometimes one needs to classify individuals into groups, but there is no available grouping information due to social desirability bias in reporting behavior like unethical or dishonest intentions or unlawful actions. Assessing hard-to-detect behaviors is useful; however it is methodologically difficult because people are unlikely to self-disclose bad actions. This paper presents an unsupervised classification methodology utilizing ordinal categorical predictor variables. It allows for classification, individual respondent ranking, and grouping without access to a dependent group indicator variable. The methodology also measures predictor variable worth (for determining target behavior group membership) at a predictor variable category-by-category level, so different variable response categories can contain different amounts of information about classification. It is asymmetric in that a “0” on a binary predictor does not have a similar impact toward signaling “membership in the target group” as a “1” has for signaling “membership in the non-target group.” The methodology is illustrated by identifying Spanish consumers filing fraudulent insurance claims. A second illustration classifies Portuguese high school student’s propensity to alcohol abuse. Results show the methodology is useful when it is difficult to get dependent variable information, and is useful for deciding which predictor variables and categorical response options are most important.     

The characteristics of non-criminals with high psychopathy traits: Are they similar to criminal psychopaths?

This study compared the findings from a sample of non-criminals with high and low psychopathy levels to published findings with criminal psychopaths and non-psychopaths. Congruent to findings with criminal psychopaths, participants with high psychopathy traits (High-P) compared to those with low psychopathy traits (Low-P) performed significantly worse on the Iowa Gambling Task, a task sensitive to orbital frontal cortex dysfunction. Moreover, the High-P group also evidenced a lack of empathy, a hallmark feature of psychopathy. These findings could not be explained by differences in estimated IQ or performance on a task sensitive to an executive functioning deficit. The discussion focuses on possible differences between non-criminal and criminal psychopaths, concluding criminal psychopaths manifest more extreme degrees of the interpersonal-affective and antisocial features of psychopathy.     

糖尿病分型与治疗：我们还需要走多远

由于糖尿病病因至今未明,虽然临床上多采用ADA糖尿病分型方法,但随着对糖尿病病因及发病机制的研究,出现了许多难以用传统的标准进行分类的疾病状态。有人提出淡化糖尿病分型的争论。笔者认为高血糖仅是一种表现,并不是疾病的本质,慢性低活度炎症状态可能是核心机制之一,机体的这种慢性低活度炎症状态可能与糖尿病肾病、抗感染免疫失控以及创伤愈合障碍有关。短时间内控制急性高血糖状态对挽救生命是关键的,但要实现长期是代谢紊乱控制、纠正不良生活习惯、减轻腹内脂肪堆积,进而降低改善机体的慢性炎症状态可能是最全面且安全的唯一措施。     

Reliability of job satisfaction measures

In this paper, we evaluate consistency in answers to subjective questions about job satisfaction and explore the implications of any inconsistencies. We do this by analyzing a cross-country data set for 6 EU countries where respondents were posed the same question about overall job satisfaction twice within the same questionnaire. We find that, on a 0–10 point ordered utility scale, 80% either classify themselves identically or in the immediate adjacent and that the differences in classification are symmetric around zero. Furthermore, we find that highly satisfied workers report most consistently. When job satisfaction is used as an explanatory variable, we show how OLS-parameter estimates provide a lower bound and IV-estimates an upper bound of the true estimate – and that the bounds are fairly tight. When job satisfaction is used as dependent variable, we generally find high consistency when parameters are highly significant in both models, while less significant or insignificant parameter estimates may change considerably. This indicates that higher significance standards may be advisable in analyses with satisfaction measures as dependent variable compared to more traditional models that are not based on subjective data.     

人格结构的中西方差异与中国人的人格特点

该文旨在通过对中西方人格结构的比较和分析揭示文化与人格结构的关系,并探寻中国人人格结构的文化意义。根据词汇学假设进行的中西方人格结构的研究结果表明,人格结构的形成是建立在对行为归类的基础之上的,中西方人格结构的差异最直接的原因就在于中西方对行为归类的差别。中国文化比较强调整体性、联系性以及评价性是造成中国人与西方人行为归类差异的原因,而更深层次的原因则是中西方文化中对人性看法的差异。中国人人格量表有着比较理想的预测效度,而且与西方大五人格量表相比更高的预测效度,这些均表明中国人人格结构的合理性。文中还提出了进一步研究的展望     

Bug distribution and statistical pattern classification

A model (called the rule space model) which permits measuring cognitive skill acquisition, diagnosing cognitive errors, detecting the weaknesses and strengths of knowledge possessed by individuals was introduced earlier. This study further discusses the theoretical foundation of the model by introducing bug distribution and hypothesis testing (Bayes' decision rules for minimum errors) for classifying subjects into their most plausible latent state of knowledge. The model is illustrated with the domain of fraction arithmetic and compared with the results obtained from a conventional artificial intelligence approach.The authors would like to acknowledge Mr. Robert Baillie for developing several computer programs used for this research.This research was sponsored by the Personnel and Training Research Program, Psychological Sciences Division, Office of Naval Research.Some of the analyses presented in this report were performed on the PLATO® system. The PLATO® system is a development of the University of Illinois and PLATO® is a service mark of the Control Data Corporation.     

Nested diagnostic classification models for multiple-choice items

This study proposes and evaluates a diagnostic classification model framework for multiple-choice items. Models in the proposed framework have a two-level nested structure which allows for binary scoring (for correctness) and polytomous scoring (for distractors) at the same time. One advantage of these models is that they can provide distractor information while maintaining the statistical properties of the correct response option. We evaluated parameter recovery through a simulation study using Hamiltonian Monte Carlo algorithms in Stan. We also discussed three approaches to implementing the proposed modelling framework for different purposes and testing scenarios. We illustrated those approaches and compared them with a binary model and a traditional nominal model through an operational study.