多级计分测验中基于残差统计量的被试拟合研究

本文提出一种多级计分项目下的个人拟合统计量R, 考察它在检测6种常见的异常作答模式(作弊、猜测、随机、粗心、创新作答、混合异常)下的表现, 并与标准化对数似然统计量l_zp进行比较。结果表明：(1) 在异常作答覆盖率较低并且异常作答类型为作弊和猜测时, R的检测率显著高于l_zp; (2) 随着测验长度和被试异常程度的增加, 两种统计量的检测率都会上升; (3) 在一些条件下, R与l_zp检测效果接近。实证数据分析进一步展示了R统计量的使用方法和过程, 结果也表明R统计量具有较好的应用前景。     

A comparative evaluation of factor- and component-based structural equation modelling approaches under (in)correct construct representations

Structural equation modelling (SEM) has evolved into two domains, factor-based and component-based, dependent on whether constructs are statistically represented as common factors or components. The two SEM domains are conceptually distinct, each assuming their own population models with either of the statistical construct proxies, and statistical SEM approaches should be used for estimating models whose construct representations correspond to what they assume. However, SEM approaches have often been evaluated and compared only under population factor models, providing misleading conclusions about their relative performance. This is partly because population component models and their relationships have not been clearly formulated. Also, it is of fundamental importance to examine how robust SEM approaches can be to potential misrepresentation of constructs because researchers may often lack clear theories to determine whether a factor or component is more representative of a given construct. Addressing these issues, this study begins by clarifying several population component models and their relationships and then provides a comprehensive evaluation of four SEM approaches – the maximum likelihood approach and factor score regression for factor-based SEM as well as generalized structured component analysis (GSCA) and partial least squares path modelling (PLSPM) for component-based SEM – under various experimental conditions. We confirm that the factor-based SEM approaches should be preferred for estimating factor models, whereas the component-based SEM approaches should be chosen for component models. Importantly, the component-based approaches are generally more robust to construct misrepresentation than the factor-based ones. Of the component-based approaches, GSCA should be chosen over PLSPM, regardless of whether or not constructs are misrepresented.     

Humanizing autonomous vehicle driving: Understanding,modeling and impact assessment

The advent of autonomous vehicles brings major changes in the transportation systems influencing the infrastructure design, the network performance, as well as driving functions and habits. The penetration rate of this new technology highly depends on the acceptance of the automated driving services and functions, as well as on their impacts on various traffic, user oriented and environmental aspects. This research aims to present a methodological framework aiming to facilitate the modelling of the behaviour of new AV driving systems and their impacts on traffic, safety and environment. This framework introduces a stepwise approach, which will be leveraged by stakeholders in order to evaluate the new technology and its components at the design or implementation phase in order to increase acceptance and favor the adoption of the new technology. The proposed framework consists of four sequential steps: i. conceptual design, ii. data collection, processing and mining, iii. modelling and iv. autonomous vehicles impact assessment. The connection between these steps is illustrated and various Key Performance Indicators are specified for each impact area. The paper ends with highlighting some conceptual and modeling challenges that may critically affect the study of acceptance of autonomous vehicles in future mobility scenarios.     

The dynamics of purchasing an electric vehicle – A prospective longitudinal study of the decision-making process

This paper presents the results of a longitudinal prospective study which followed 113 people interested in the purchase of an electric vehicle for a period of two months. Based on an adapted stage model of self-regulated behavioral change (Bamberg, 2013b), a short online questionnaire with a stage diagnostic and the measurement of central model constructs was administered to the participants every second day. The analysis shows that 85% of transitions between the stages occur along the paths of the stage model. Stage transitions are preceded by increases in goal intentions and implementation intentions during the week before the transition. Intentions are predicted by most of the expected model constructs, but the effects were different on the between-person and the within-person level. The average stage durations are between two and three weeks. Implications of the study for research on stage models and practice are discussed.     

Living in Two Worlds. How ‘Jungian’ am I?

As a so‐called ‘Developmental Jungian’ the author of this paper was raised bilingual ‐ speaking both psychoanalytic and Jungian languages. Early on in her training an analysand brought a dream which seemed to capture an inherent tension regarding the analyst's role in the analytic relationship. The paper is a personal exploration of the potentially creative nature of this tension through focussing on the dream and the work with the dreamer.     

Persistent career indecision over time: Links with personality,barriers, self-efficacy,and life satisfaction

Taking control over one's career requires the ability to make career decisions; thus, remaining in a state of career indecision is problematic. However, the stability of career indecision has not yet been investigated using advanced statistical modeling approaches. We present two studies of German university students applying three-wave, longitudinal designs. Study 1 investigated the stability of career indecision by means of latent state-trait analysis within two samples with different time lags (Sample 1: N = 363, 7 weeks; Sample 2: N = 591, 6 months). The results indicated that career indecision was determined by a stable component (i.e., trait career indecisiveness) that was associated with lower core self-evaluations, lower occupational self-efficacy, and higher perceived career barriers. Study 2 (N = 469) examined career indecision over one year. We found that the stable career indecision component explained 5% of the variance in student life satisfaction beyond self-evaluated generalized indecisiveness.     

Developing agency through good work: Longitudinal effects of job autonomy and skill utilization on locus of control

An internal locus of control has benefits for individuals across multiple life domains. Nevertheless, whether it is possible to enhance an individual's internal locus of control has rarely been considered. The authors propose that the presence of job autonomy and skill utilization in work can enhance internal locus of control, both directly and indirectly via job satisfaction. Three waves of data over a four-year period from the Household, Income and Labour Dynamics in Australia Survey (N = 3045) were analyzed. Results showed that job autonomy directly shaped internal locus of control over time, as did job satisfaction. Skill utilization did not play a role in terms of affecting locus of control, and the indirect effects of both job autonomy and skill utilization via job satisfaction were weak. This study suggests the importance of job autonomy in promoting the development of an employee's internal locus of control.     

Conceptualizations of Giftedness and the Development of Talent: Implications for Counselors

The authors present a historical perspective on giftedness, highlighting the impact of key research studies on practice, research, and policy. A comprehensive model is presented emphasizing that giftedness is domain specific and developmental and involves the cultivation of psychosocial as well as cognitive skills. Implications for counselors are discussed, specifically which psychosocial issues and skills should be the focus of counseling at each stage of talent development and what counselors can do to support the development of gifted students.     

Acquiescence in personality questionnaires: Relevance,domain specificity,and stability

Acquiescence, which is defined as agreeing to items regardless of content, is a well-known bias in self-report instruments. This paper investigates the relevance, domain specificity, and the stability of acquiescence in personality questionnaires. Data from two large samples representative for the German (N = 1999) and for the Austrian adult population (N = 3266) were investigated with structural equation models. In both studies respondents answered, besides others, a short Big Five inventory. The three core findings are: (1) acquiescence systematically affects the variance of personality items and biases the association with other variables, (2) acquiescence is consistent across different question types, and (3) acquiescence in personality items is moderately stable over time. Implications for research and the application of personality questionnaires are discussed.