A stochastic multidimensional scaling procedure for the empirical determination of convex indifference curves for preference/choice analysis

The vast majority of existing multidimensional scaling (MDS) procedures devised for the analysis of paired comparison preference/choice judgments are typically based on either scalar product (i.e., vector) or unfolding (i.e., ideal-point) models. Such methods tend to ignore many of the essential components of microeconomic theory including convex indifference curves, constrained utility maximization, demand functions, et cetera. This paper presents a new stochastic MDS procedure called MICROSCALE that attempts to operationalize many of these traditional microeconomic concepts. First, we briefly review several existing MDS models that operate on paired comparisons data, noting the particular nature of the utility functions implied by each class of models. These utility assumptions are then directly contrasted to those of microeconomic theory. The new maximum likelihood based procedure, MICROSCALE, is presented, as well as the technical details of the estimation procedure. The results of a Monte Carlo analysis investigating the performance of the algorithm as a number of model, data, and error factors are experimentally manipulated are provided. Finally, an illustration in consumer psychology concerning a convenience sample of thirty consumers providing paired comparisons judgments for some fourteen brands of over-the-counter analgesics is discussed.     

Axiomatic and numerical conjoint measurement: An evaluation of diagnostic efficacy

Synthetic data are used to examine how well axiomatic and numerical conjoint measurement methods, individually and comparatively, recover simple polynomial generators in three dimensions. The study illustrates extensions of numerical conjoint measurement (NCM) to identify and model distributive and dual-distributive, in addition to the usual additive, data structures. It was found that while minimum STRESS was the criterion of fit, another statistic, predictive capability, provided a better diagnosis of the known generating model. That NCM methods were able to better identify generating models conflicts with Krantz and Tversky's assertion that, in general, the direct axiom tests provide a more powerful diagnostic test between alternative composition rules than does evaluation of numerical correspondence. For all methods, dual-distributive models are most difficult to recover, while consistent with past studies, the additive model is the most robust of the fitted models.Douglas Emery is now at the Krannert Graduate School of Management, Purdue University, West Lafayette, IN, on leave from the University of Calgary.     

情绪分享和感知恋人回应对亲密关系满意度的影响

研究通过问卷星收集了150对异性恋情侣的情绪分享、感知恋人回应、亲密关系满意度的数据,并采用行动者-对象互依模型进行统计分析。结果显示：（1）情绪分享通过感知恋人回应的中介作用影响亲密关系满意度。女性的积极情绪分享与男性的消极情绪分享直接正向影响自身亲密关系满意度。（2）男性的积极情绪分享正向影响女性的亲密关系满意度。研究揭示了亲密关系中情绪分享和感知恋人回应对关系满意度的影响特点。     

钦佩感：一种见贤思齐的积极情绪

钦佩感是对优秀他人或榜样的一种高度喜欢和尊敬, 是看到他人的优秀行为或品质时所产生的一种积极情绪, 其典型成分是欣赏和鼓舞。他人的优秀能力、美德、积极态度、自我提升动机、相似的价值观等因素影响钦佩感的产生。美德钦佩感会导致后叶催产素分泌, 和能力钦佩感分别激发不同但又相互重叠的脑区。钦佩感具有激励作用, 提高自我效能感和结果期望并影响其职业意向, 激发个体的亲社会动机与行为。拓展钦佩感的概念与成分、辨析与崇拜的相似与不同、开展钦佩感的应用研究以及跨文化或本土化研究等是该领域未来重要的研究方向。     

Infants’ behavioral styles in joint attention situations and parents’ socio-economic status

In this study the eco-cultural model of parenting (Keller, H. (2007). Cultures of infancy. Mahwah, NJ: Erlbaum) was applied to the study of joint attention behavior of children from families with different socio-economic status (SES). It was hypothesized that infants’ early communication styles would differ with SES reflecting more independent or interdependent interactions with their caregivers. It was also hypothesized that infants would use the same types of behaviors whether they have declarative or imperative communication goals. The Early Social Communication Scales (ESCS, Mundy et al., 2003) was administered to 103 typically developing infants of 12 months (approximately half of them siblings of children with autism). A factor analysis, yielding four behavioral factors, namely pointing, eye contact, actions and following points, confirmed the hypothesis that infants use behaviors consistently across situations independent of their communicative intent. MANOVAs (comprising parental education and income) revealed that higher SES infants showed actions more frequently in the ESCS whereas lower SES infants followed experimenter's points more frequently. The results are discussed in the context of presumably differing socialization goals for infants and the divergent contribution of parental education and income that seem to have additive contribution to some factors (actions, following points) but divergent contributions to others (pointing, eye contact).     

Stopping rules for multi-category computerized classification testing

Computerized classification testing (CCT) aims to classify persons into one of two or more possible categories to make decisions such as mastery/non-mastery or meet most/meet all/exceed. A defining feature of CCT is its stopping criterion: the test terminates when there is enough confidence to make a decision. There is abundant research on CCT with a single cut-off, and two common stopping criteria are the sequential probability ratio test (SPRT) statistic and the generalized likelihood ratio statistic (GLR). However, there is a relative scarcity of research extending the SPRT to the multi-hypothesis case for when there is more than one cut-off. In this paper, we propose a new multi-category GLR (mGLR) statistic as well as a stochastically curtailed version of the CCT with three or more categories. A simulation study was conducted to show that the mGLR statistic outperformed the existing stopping rules by generating shorter average test length without sacrificing classification accuracy. Results also revealed that the stochastically curtailed mGLR successfully increased test efficiency in certain testing conditions.     

Changing the Criminal Justice System Response to Sexual Assault: An Empirical Study of a Participatory Action Research Project

In jurisdictions throughout the United States, thousands of sexual assault kits (SAKs; also known as a “rape kits”) have not been submitted by the police for forensic DNA testing. DNA evidence may be helpful to sexual assault investigations and prosecutions by identifying perpetrators, revealing serial offenders through DNA matches across cases, and exonerating those who have been wrongly accused. This paper describes a longitudinal action research project conducted in Detroit, Michigan after that city discovered approximately 11,000 untested sexual assault kits in a police department storage facility. We conducted a root cause analysis to examine individual, organizational, community, and societal factors that contributed to the development of the rape kit backlog in Detroit. Based on those findings, we implemented and evaluated structural changes to increase staffing, promote kit testing, and retrain police and prosecutors so that cases could be reopened for investigation and prosecution. As we conducted this work, we also studied how this action research project impacted the Detroit criminal justice system. Participating in this project changed stakeholders’ attitudes about the utility of research to address community problems, the usefulness of DNA evidence in sexual assault cases, and the impact of trauma on survivors. The results led to new protocols for SAK testing and police investigations, and new state legislation mandating SAK forensic DNA testing.     

Enhancing the care of children with chronic diseases through the narratives of patient,physician, nurse and carer

We tested the hypothesis that a narrative approach may enhance a bio‐psycho‐social model (BPS) in caring for chronically ill children. Forty‐eight narratives were collected from 12 children with six different medical conditions, their mothers, physicians, and nurses. By a textual analysis, narratives were classified on their predominant focus as disease (biological focus), illness (psychologic focus), or sickness (social focus). Sixty‐one percent of narrative’ text were classified as illness, 28% as disease and 11% as sickness. All narratives had a degree of illness focus. Narratives by patients and physicians on the one hand, and nurses’ and mothers’ on the other were disease focused. Narratives were also evaluated with respect to the type of medical condition: Illness was largely prevalent in all but Crohn’s disease and HIV infection, the latter having a predominance of sickness most probably related to stigma. Narrative exploration proved a valuable tool for understanding and addressing the needs of children with complex conditions. Narrative approaches allow identification of the major needs of different patients according to health conditions and story tellers. In the narratives, we found a greater illness and disease focus and surprisingly a low sickness focus, except with HIV stories. Narrative medicine provides a tool to strengthen the BPS model in health care.     

Discerning Mouse Trajectory Features With the Drift Diffusion Model

Mouse tracking, a new action-based measure of behavior, has advanced theories of decision making with the notion that cognitive and social decision making is fundamentally dynamic. Implicit in this theory is that people's decision strategies, such as discounting delayed rewards, are stable over task design and that mouse trajectory features correspond to specific segments of decision making. By applying the hierarchical drift diffusion model and the Bayesian delay discounting model, we tested these assumptions. Specifically, we investigated the extent to which the “mouse-tracking” design of decision-making tasks (delay discounting task, DDT and stop-signal task, SST) deviate from the standard “keypress” design of decision making tasks. We found remarkable agreement in delay discounting rates (intertemporal impatience) obtained in the keypress and mouse-tracking versions of DDT (ρ = 0.90) even though these tasks were given about 1 week apart. Rates of evidence accumulation converged well in the two versions (DDT, ρ = .86; SST, ρ = .55). Omission/commission error in SST showed high agreement (ρ = .42, ρ = .53). Mouse-motion features such as maximum velocity and AUC (area under the curve) correlated well with nondecision time (ρ = −.42) and boundary separation (ρ = .44)—the amount of information needed to accumulate prior to making a response. These results indicate that the response time (RT) and motion-based decision tasks converge well at a fundamental level, and that mouse-tracking features such as AUC and maximum velocity do indicate the degree of decision conflict and impulsivity.