Assessment of dental anxiety: A facet approach

Dental anxiety is a complicated phenomenon, and its multicomponent nature is often not acknowledged in existing measurement instruments. Using a facet design, a new Dental Anxiety Inventory (DAI) was constructed. Facets chosen were: time (made up of four elements: at home, on your way to the denstist, in the denstist's waiting room, in the dental chair), situation (three elements: introductory aspects, dentist-patient interaction, actual dental treatment), and reaction (three elements: subjective feelings, physical reactions, cognitive reactions). Psychometric qualities of the DAI are good. The internal structure of the DAI was studied by linear and nonlinear techniques, and was partially recovered from the data. The construct and criterion validity of the DAI was supported in several studies.     

At the Edge of Eternity's Shadows: Scaling the Fractal Continuum from Lower into Higher Space

In this paper, I elaborate the hyperspatial implications of the fractal-scaling scheme that I introduced previously. Four case examples where out-of-body experiencers reported heightened and amplified visual capacities are correlated with this explanatory model. Three of these cases are identified as including an additional hyperspace signifier, the reported capacity to see through solid and opaque physical obstructions. One of these cases included yet another hyperspace signifier, the reported capacity to pass through such obstructions. Additional evidence supportive of this thesis is drawn from the literature on ecstatic experience, including out-of-body, near-death, and other varieties of mystical or visionary experience, and from that on psychedelic experience. Yet other hyperspace signifiers reported by ecstatic voyagers are also considered, including sensations of seeing outward spherically in 360 degrees and of seeing on all sides of three-dimensional solids simultaneously.     

Detection of differential item functioning in Rasch models by boosting techniques

Methods for the identification of differential item functioning (DIF) in Rasch models are typically restricted to the case of two subgroups. A boosting algorithm is proposed that is able to handle the more general setting where DIF can be induced by several covariates at the same time. The covariates can be both continuous and (multi‐)categorical, and interactions between covariates can also be considered. The method works for a general parametric model for DIF in Rasch models. Since the boosting algorithm selects variables automatically, it is able to detect the items which induce DIF. It is demonstrated that boosting competes well with traditional methods in the case of subgroups. The method is illustrated by an extensive simulation study and an application to real data.     

Offender and Offence Characteristics of School Shooting Incidents

School shootings are a concern due to their impact in the local community. This paper aimed to (a) establish frequent characteristics of the offender and offence, (b) explore the differences between offenders who are over the age of 18 years and those who are younger, and (c) consider the underlying themes of the offence characteristics. Data were collected on 28 cases through accessing resources such as West Law and case studies. The majority of the offenders were Caucasian and US citizens and suffered from depression. Their offences were primarily well planned, involved more than three deaths, and resulted in the offender committing suicide. Pearson's chi‐square test and Fisher's exact test identified significant differences between the two age groups. Offenders who were 18 years of age or under were more likely to experience depression, be US citizens and be linked to the school. Additionally, offenders who were 18 years of age or under were more likely to have stolen their weapons and made threats prior to the incident. Smallest space analysis revealed four thematic regions in relation to the offence characteristics: making an impact, delivering a message, doing unrestrained activity, and targeting specific individuals. These findings have implications for risk assessment and furthering understanding. Copyright © 2015 John Wiley & Sons, Ltd.     

Optimal designs for the generalized partial credit model

Analysing ordinal data is becoming increasingly important in psychology, especially in the context of item response theory. The generalized partial credit model (GPCM) is probably the most widely used ordinal model and has found application in many large-scale educational assessment studies such as PISA. In the present paper, optimal test designs are investigated for estimating persons’ abilities with the GPCM for calibrated tests when item parameters are known from previous studies. We find that local optimality may be achieved by assigning non-zero probability only to the first and last categories independently of a person's ability. That is, when using such a design, the GPCM reduces to the dichotomous two-parameter logistic (2PL) model. Since locally optimal designs require the true ability to be known, we consider alternative Bayesian design criteria using weight distributions over the ability parameter space. For symmetric weight distributions, we derive necessary conditions for the optimal one-point design of two response categories to be Bayes optimal. Furthermore, we discuss examples of common symmetric weight distributions and investigate under what circumstances the necessary conditions are also sufficient. Since the 2PL model is a special case of the GPCM, all of these results hold for the 2PL model as well.     

Distance stability analysis in multidimensional scaling using the jackknife method

Stability or sensitivity analysis is an important topic in data analysis that has received little attention in the application of multidimensional scaling (MDS), for which the only available approaches are given in terms of a coordinate‐based analytical jackknife methodology. Although in MDS the prime interest is in assessing the stability of the points in the configuration, this methodology may be influenced by imprecisions resulting from the inherently necessary Procrustes method. This paper proposes an analytical distance‐based jackknife procedure to study stability and cross‐validation in MDS in terms of the jackknife distances, which is not influenced by the Procrustes method. For each object, the corresponding jackknife estimated points are considered as naturally clustered points, and stability and cross‐validation are analysed in terms of the MDS distances arising from the jackknife procedure, on the basis of a weighted cluster‐MDS algorithm. A jackknife‐relevant configuration is also proposed for cross‐validation in terms of coordinates, in a cluster‐MDS framework.     

Influence of Proactive Personality on Career Self‐Efficacy

This study examined the relationship between proactive personality and career decision‐making self‐efficacy. In Study 1, the authors validated the Proactive Personality Scale–Korean Short Form, using the Rasch model with 315 participants, and found that fit statistics, point‐measure correlations, and item difficulty estimates satisfy the construct validity criterion. In Study 2, the authors administered the Proactive Personality Scale, Career Decision‐Making Self‐Efficacy Scale, and Career Search Self‐Efficacy Scale to 296 freshman and sophomore college students. Hierarchical regression analyses showed that proactive personality scores explain additional variance in both career decision‐making self‐efficacy and career search self‐efficacy scores. Implications for theory and practice are discussed.     

应用Rasch模型测试和分析儿童入学准备状态

本研究的目的在于应用Rasch模型编制和分析数学入学准备测验,从而分析Rasch模型的有效性和优势。自编数学入学准备测试,对150名平均年龄为6.6岁的儿童进行测查,应用Rasch模型对题目和评分等级做出修正并分析结果。结果表明修正后的测试具有较好的信效度,较好地拟合了Rasch模型,评分等级设置合理,测试的整体难度相对较低。儿童的Rasch分数和性别无关,但受到年龄、家庭社会经济地位的影响。相对于经典测量理论而言,应用Rasch模型进行入学准备测试的编制和分析具有优势。     

垂直量尺化中的参数标定方法及其性能比较

在使用项目反应理论进行量尺化的语境下, 参数标定方法是垂直量尺化结果的一个至关重要的影响因素。目前的参数标定研究就部分标定方法的相对性能获得了较一致的结果, 就如何实现更佳量尺化也提出了很多新的标定方法。除了在既有框架内继续探索, 以形成完整的研究体系, 未来的研究应结合相关学科, 在深入了解学业增长的性质的基础上探究标定方法的性能, 并应考察特定的标定方法和特定的研究条件、量尺化语境之间的最佳匹配关系。     

多维Rasch模型在维度分数报告中的应用—对带宽-保真度困境的解决

分别采用四维度和十五维度Rasch模型分析包含项目内多维度结构的科学测验数据,估计两种维度结构下维度分数的信度.结果表明,对比相应的单维模型而言,四维度与十五维度Rasch模型均能够极大提高各内容维度上分数估计的信度.四维度与十五维度Rasch模型拟合结果的比较表明,对于总长度固定的测验,维度数目的增加能够补偿子维度长度减少引起的信度损失.但是这一作用必须以维度间较高的相关性为前提.