A latent class approach to fitting the weighted Euclidean model,clascal

A weighted Euclidean distance model for analyzing three-way proximity data is proposed that incorporates a latent class approach. In this latent class weighted Euclidean model, the contribution to the distance function between two stimuli is per dimension weighted identically by all subjects in the same latent class. This model removes the rotational invariance of the classical multidimensional scaling model retaining psychologically meaningful dimensions, and drastically reduces the number of parameters in the traditional INDSCAL model. The probability density function for the data of a subject is posited to be a finite mixture of spherical multivariate normal densities. The maximum likelihood function is optimized by means of an EM algorithm; a modified Fisher scoring method is used to update the parameters in the M-step. A model selection strategy is proposed and illustrated on both real and artificial data.The second author is supported as Bevoegdverklaard Navorser of the Belgian Nationaal Fonds voor Wetenschappelijk Onderzoek.     

A thurstonian pairwise choice model with univariate and multivariate spline transformations

A probabilistic choice model is developed for paired comparisons data about psychophysical stimuli. The model is based on Thurstone's Law of Comparative Judgment Case V and assumes that each stimulus is measured on a small number of physical variables. The utility of a stimulus is related to its values on the physical variables either by means of an additive univariate spline model or by means of multivariate spline model. In the additive univariate spline model, a separate univariate spline transformation is estimated for each physical dimension and the utility of a stimulus is assumed to be an additive combination of these transformed values. In the multivariate spline model, the utility of a stimulus is assumed to be a general multivariate spline function in the physical variables. The use of B splines for estimating the transformation functions is discussed and it is shown how B splines can be generalized to the multivariate case by using as basis functions tensor products of the univariate basis functions. A maximum likelihood estimation procedure for the Thurstone Case V model with spline transformation is described and applied for illustrative purposes to various artificial and real data sets. Finally, the model is extended using a latent class approach to the case where there are unreplicated paired comparisons data from a relatively large number of subjects drawn from a heterogeneous population. An EM algorithm for estimating the parameters in this extended model is outlined and illustrated on some real data.The first author is supported as Bevoegdverklaard Navorser of the Belgian Nationaal Fonds voor Wetenschappelijk Onderzoek. The authors are indebted to Ulf Böckenholt and Yoshio Takane for useful comments on an earlier draft of this paper.     

A latent class unfolding model for analyzing single stimulus preference ratings

A multidimensional unfolding model is developed that assumes that the subjects can be clustered into a small number of homogeneous groups or classes. The subjects that belong to the same group are represented by a single ideal point. Since it is not known in advance to which group of class a subject belongs, a mixture distribution model is formulated that can be considered as a latent class model for continuous single stimulus preference ratings. A GEM algorithm is described for estimating the parameters in the model. The M-step of the algorithm is based on a majorization procedure for updating the estimates of the spatial model parameters. A strategy for selecting the appropriate number of classes and the appropriate number of dimensions is proposed and fully illustrated on some artificial data. The latent class unfolding model is applied to political science data concerning party preferences from members of the Dutch Parliament. Finally, some possible extensions of the model are discussed.The first author is supported as Bevoegdverklaard Navorser of the Belgian Nationaal Fonds voor Wetenschappelijk Onderzoek. Part of this paper was presented at the Distancia meeting held in Rennes, France, June 1992.     

柯林斯语义层次网络模型的实验研究

应用语义验证法对柯林斯与奎利安的语义层次网络模型进行研究,结果表明:(1)柯林斯等人的语义层次网络模型不完全适用于人脑的信息加工;(2)被试对主语所指称客体的熟悉程度是决定语义验证时间的一个重要因素;(3)被试提取概念各属性的时间并非完全由属性储存的位置决定的。     

The logic of the medical research article

As do all forms of science, medical theories have a factual as well as a logical basis. New information is presented in medical research articles. These papers have three separate arguments: the argument of the hypothesis, the argument of the experimental protocol, and the argument of the hypothesis's judgment. These arguments may be examples of the hypothetico-deductive or confirmational model of scientific inference. The logical form of these arguments are informal and inductive rather than formal and deductive. Understanding the nature of the logic of the medical research article may help avoid erroneous conclusions.     

A Brief History of Metacognitive Therapy: From Cognitive Science to Clinical Practice

Metacognitive therapy (MCT) is proving to be an effective treatment for anxiety and depression with effects that may exceed CBT. It has been described as a paradigm shift in psychotherapy in its theory-driven cognitive science approach and systematic development and evaluation. MCT was developed by Adrian Wells based on an information processing theory, the Self-Regulatory Executive Function model by Wells and Matthews. MCT theory formulates psychological disorders as sharing common causal factors under the influence of metacognition, representing a particular top-down model of biases in cognitive regulation. A key clinical implication was that a core set of interventions could be developed to impact a wide range of symptoms and disorders. In this paper, we trace the historical development of MCT and the major studies that informed theory and practice with the aim of introducing clinicians and researchers to this area and to understand why the metacognitive approach has developed into a treatment that is proving to be potentially more effective than current gold-standard treatments. In doing so, we will draw out the distinctive features of the approach and explore how this might offer a blueprint for scientific advancement in clinical psychology and psychotherapy.     

Self-compassion reduces parental burnout: Mediation roles of parental psychological control and support

This study investigated the mediating role of parental psychological control (PPC) and support in the relationship between self-compassion and parental burnout syndrome. The study participants included 1185 Vietnamese parents who completed questionnaires regarding demographic information, parental burnout, self-compassion, parental support of the child, and PPC. We used data analyses, including structural equation modeling, to test the mediation roles of PPC and parental support of the child. Our main findings include: (1) self-compassion had a significant negative effect on parental burnout; (2) the mediation roles of PPC and parental support of the child were also significant. These results suggest that parents with high self-compassion tend to provide more support for children in daily parenting, which helps reduce parental burnout. In contrast, parents with low self-compassion were more likely to use PPC, which exacerbated their burnout. The results from this study provide suggestions for creating effective interventions in the family context to reduce parental burnout and improve parenting effectiveness.     

Dyadic processes of relational turbulence theory

This study tested dyadic processes of relational turbulence theory (RTT) in heterosexual marriages. We tested propositions 1, 2, and 5 of RTT, which propose that uncertainty about the marriage biases cognitive appraisals, and that interference from a partner heightens negative emotions, both of which culminate in relational turbulence for spouses. Guided by these propositions, husbands' and wives' (N = 510; 255 marital dyads) dyadic cognitive and emotional processes were estimated using the actor-partner interdependence mediation model. Consistent with theoretical propositions, we found evidence for actor-actor indirect effects; for both husbands and wives (a) the effect of spouses' relationship uncertainty on their own relational turbulence was mediated by their own biased cognitive appraisals, and (b) the effect of spouses' experienced interference on their own relational turbulence was mediated by their own anger from communicating in the marriage. However, controlling for actor-actor indirect effects, partner-defined processes (i.e., actor-partner and partner-actor indirect effects) uniquely explained husbands' and wives' relational turbulence.