卡方自动交叉检验在人群细分中的应用

卡方自动交叉检验（CHi-squaredAutomaticInteractionDetector,CHAID）是一种定性的统计分类技术,主要解决根据一个因变量的不同反应确定若干预测变量的特征问题。这种算法模型可广泛应用于社会调查和市场细分中,根据不同的目的细分人群。该文主要介绍了CHAID算法模型的概念和发展,理论基础和应用过程,以及其效度检验方法,并将其与Logit模型等作了比较,指出其优势和局限。最后提出了研究展望     

不同链接函数下多级评分认知诊断模型的比较及应用研究

认知诊断测验因具有传统测验所不具备的诊断功能而日益受到重视。当前多级评分认知诊断模型开发中,研究者采用不同的链接函数（Link Function）开发出不同的多级评分认知诊断模型。本研究基于局部或相邻类别链接函数(Local or Adjacent Categories Link Function)的思想,开发出多级评分认知诊断模型LC-DINA研究采用Monte Carlo模拟研究与实证应用研究相结合的方法,将新开发模型与已有模型进行比较并应用于国际数学与科学评估（TIMMS）中,为实际应用者提供了借鉴。     

A pseudo-dynamic search ant colony optimization algorithm with improved negative feedback mechanism

To solve low convergence precision and slow convergence speed, a pseudo-dynamic search ant colony optimization algorithm with improved negative feedback mechanism (PACON) is proposed. Firstly, the algorithm introduces an angle in the pheromone transfer rule. Through the rule for calculating the angle, multiple cities with smaller angles are also included in the next candidate city list. It affects the probability of city selection and enhances the algorithm’ performance to avoid local optimization. Secondly, the algorithm updates the pheromone concentrations on the worst and optimal path simultaneously, and enhances the weights of the pheromone concentrations on the optimal path. It improves the convergence speed of the algorithm. Based on experiments adopting TSPLIB data sets, the results demonstrate the improved algorithm improves the convergence accuracy by at least 1.26% and increases the convergence speed by at least 9.5%, both on large-scale and small-scale urban data. The novel algorithm will improve convergence precision and speed better.     

机器学习在抑郁症领域的应用

抑郁症患者疾病意识的不足以及早期筛查方法的缺乏导致患者在被诊断时大多已发展至重性抑郁障碍。为改善现状, 近年来机器学习被逐渐应用到抑郁症的早期预测、早期识别、辅助诊断和治疗决策中。在应用中, 机器学习模型准确性的影响因素包括样本集种类及规模、特征工程、算法类型等。建议未来将机器学习进一步融入医疗健康系统及移动应用程序等, 不断优化机器学习模型, 通过充分挖掘患者健康数据来改善抑郁症的预防、识别、诊断和治疗等相关问题。     

First-Order Learning Models With the GDINA: Estimation With the EM Algorithm and Applications

In learning environments, understanding the longitudinal path of learning is one of the main goals. Cognitive diagnostic models (CDMs) for measurement combined with a transition model for mastery may be beneficial for providing fine-grained information about students’ knowledge profiles over time. An efficient algorithm to estimate model parameters would augment the practicality of this combination. In this study, the Expectation–Maximization (EM) algorithm is presented for the estimation of student learning trajectories with the GDINA (generalized deterministic inputs, noisy, “and” gate) and some of its submodels for the measurement component, and a first-order Markov model for learning transitions is implemented. A simulation study is conducted to investigate the efficiency of the algorithm in estimation accuracy of student and model parameters under several factors—sample size, number of attributes, number of time points in a test, and complexity of the measurement model. Attribute- and vector-level agreement rates as well as the root mean square error rates of the model parameters are investigated. In addition, the computer run times for converging are recorded. The result shows that for a majority of the conditions, the accuracy rates of the parameters are quite promising in conjunction with relatively short computation times. Only for the conditions with relatively low sample sizes and high numbers of attributes, the computation time increases with a reduction parameter recovery rate. An application using spatial reasoning data is given. Based on the Bayesian information criterion (BIC), the model fit analysis shows that the DINA (deterministic inputs, noisy, “and” gate) model is preferable to the GDINA with these data.     

Were the Victorians cleverer than us? The decline in general intelligence estimated from a meta-analysis of the slowing of simple reaction time

The Victorian era was marked by an explosion of innovation and genius, per capita rates of which appear to have declined subsequently. The presence of dysgenic fertility for IQ amongst Western nations, starting in the 19th century, suggests that these trends might be related to declining IQ. This is because high-IQ people are more productive and more creative. We tested the hypothesis that the Victorians were cleverer than modern populations, using high-quality instruments, namely measures of simple visual reaction time in a meta-analytic study. Simple reaction time measures correlate substantially with measures of general intelligence (g) and are considered elementary measures of cognition. In this study we used the data on the secular slowing of simple reaction time described in a meta-analysis of 14 age-matched studies from Western countries conducted between 1889 and 2004 to estimate the decline in g that may have resulted from the presence of dysgenic fertility. Using psychometric meta-analysis we computed the true correlation between simple reaction time and g, yielding a decline of − 1.16 IQ points per decade or − 13.35 IQ points since Victorian times. These findings strongly indicate that with respect to g the Victorians were substantially cleverer than modern Western populations.     

Schizotypy,cognitive performance,and genetic risk for schizophrenia in a non-clinical population

Schizophrenia risk alleles are expected to mediate effects on cognitive task performance, and aspects of personality including schizotypy, in nonclinical populations. We investigated how 32 of the best-validated schizophrenia risk alleles, singly and as summed genetic risk, were related to measures of schizotypal personality and measures of two aspects of cognitive performance, verbal skills (vocabulary) and visual-spatial skills (mental rotation), in healthy individuals. Summed genetic risk score was not associated with levels of total schizotypy or its three main subscales. Similarly, genotypic variation at none of the individual risk loci was related to cognitive performance measures, after correction for multiple tests. Higher overall genetic risk score was, however, associated with lower performance on the mental rotation test in males, with a broad set of loci contributing to this effect. These results imply that there is a lack of linear, genetically-based continuity connecting schizotypal cognition with the expression of schizophrenia itself, and indicate that, for males, higher genetic risk of schizophrenia exerts negative effects on visual-spatial skills, as measured by mental rotation.     

The general factor of personality: Substance or artefact?

While it is now widely recognized that a general factor (GFP) can be extracted from most personality data, this finding has been subject to numerous critiques: (1) that the GFP is an artefact due to socially desirable responding; (2) that it is factorially indeterminate; (3) that it can be more parsimoniously modelled using blended variables; (4) that it shows less genetic variance due to dominance than should be true of a fitness trait; (5) that it correlates more weakly with g than would be predicted from Life History theory; (6) that it cannot be recovered across personality inventories. We present new evidence and argument to show that each of these critiques is open to reasonable doubt.     

Perception of risk in genetic counseling

Abstract

Genetic counseling is a psychological process of communicating and perceiving information about risks. As such, it is important to assess how information is understood by counselees and how psychological factors affect risk perception. Subjects were 76 patients at a genetic clinic whose understanding of genetic counseling was assessed, along with their motivation and way of thinking about risks. Results indicated that subjective interpretations of recurrence risks are better predictors of their reproductive intentions than the “objective” risks. Also, specific cognitive and motivational factors appear to explain much of the variance in risk perception in genetic counseling. The results have important implications for how counseling is conducted, as well as for theoretical issues about cognitive processes.     

Genetic Indigenisation in ‘The People of the British Isles’

In 2007, Channel 4 screened Face of Britain, a documentary about the genetic mapping of Britain. Face of Britain promised to reveal ‘who we really are’ by tracing genetic links back to ancient Celts, Anglo-Saxons, Vikings and Normans. This article situates Face of Britain within the wider racial and national politics that it is invariably caught up in, and examines how ‘race’ and racial thinking are reconfigured in ways that are both ‘old’ and ‘new’. Face of Britain constitutes an interesting case study to examine how ideas of indigeneity are produced and naturalised in scientific discourses and practices. Here, indigeneity is mobilised through three sub-narratives: the ‘vanishing indigene’; the promise of facial recognition; and DNA and national relatedness. The analysis reveals how some people of the British Isles are naturalised as indigenous by virtue of their ancestral presence in this land through a combination of genetic and photographic technologies. In short, blood and soil are intertwined, with genes as mediators between ancestors and contemporary inhabitants of Britain. Furthermore, the invisible genetic connection is made visible through the creation of ‘average faces of Britain’, which is considered here as a contemporary version of physiognomy. In conclusion, Face of Britain testifies to the reconfiguration of ‘racial thinking’ in contemporary science, through what ultimately amounts to the genetic indigenisation of white Britons. Consequently, this study lends itself to racialised politics of land claims that resonate with, but are different from, indigenous politics in other contexts, namely with regards to the relationship to whiteness.