The study of early emotion processing in the frontal area using a two-dipole source model

The present study explored early emotion processing in the frontal area using the two-dipole source model. The 21-channel recordings of event-related potentials (ERPs) produced by a pure tone were analyzed in order to assess information processing. In the test conditions, the pure tone followed the presentation of one of two unpleasant sounds to enhance anxiety. In the control condition, only the pure tone was presented. There were two groups of eight subjects, one with low scores for trait anxiety and one with high scores. The ERPs were separately averaged for the groups, as well as for the high- and low-anxiety sound and control session. A negative peak around 120 ms (C2) and a positive peak around 280 ms (C5) after stimulus onset were identified in all the sessions. The two-dipole source model was applied to these two components. In the C2 component, dipole sources were located in the left frontal area in the control sessions, and in the right frontal area in the high-anxiety sessions. This activation pattern was clearer in the group with low trait anxiety. In contrast, with the C5 component, lateralization of the dipole source in the frontal area was not seen. These findings suggest that the frontal area is involved in early emotion processing. A dual-stage model of emotion processing is therefore proposed.     

Elementary Classes in Basic Modal Logic

Dealing with topics of definability, this paper provides some interesting insights into the expressive power of basic modal logic. After some preliminary work it presents an abstract algebraic characterization of the elementary classes of basic modal logic, that is, of the classes of models that are definable by means of (sets of) basic modal formulas. Taking that for a start, the paper further contains characterization results for modal universal classes and modal positive classes.     

A multistage ranking model

In this paper, we propose a (n–1)² parameter, multistage ranking model, which represents a generalization of Luce's model. We propose then×n item-rank relative frequency matrix (p-matrix) as a device for summarizing a set of rankings. As an alternative to the traditional maximum likelihood estimation, for the proposed model we suggest a method which estimates the parameters from thep-matrix. An illustrative numerical example is given. The proposed model and its differences from Luce's model are briefly discussed. We also show some specialp-matrix patterns possessed by the Thurstonian models and distance-based models.     

Generalized latent trait models

In this paper we discuss a general model framework within which manifest variables with different distributions in the exponential family can be analyzed with a latent trait model. A unified maximum likelihood method for estimating the parameters of the generalized latent trait model will be presented. We discuss in addition the scoring of individuals on the latent dimensions. The general framework presented allows, not only the analysis of manifest variables all of one type but also the simultaneous analysis of a collection of variables with different distributions. The approach used analyzes the data as they are by making assumptions about the distribution of the manifest variables directly.     

Bayesian analysis of order-statistics models for ranking data

In this paper, a class of probability models for ranking data, the order-statistics models, is investigated. We extend the usual normal order-statistics model into one where the underlying random variables follow a multivariate normal distribution. Bayesian approach and the Gibbs sampling technique are used for parameter estimation. In addition, methods to assess the adequacy of model fit are introduced. Robustness of the model is studied by considering a multivariate-t distribution. The proposed method is applied to analyze the presidential election data of the American Psychological Association (APA).The author is grateful to K. Lam, K.F. Lam, the Editor, an associate editor, and three reviewers for their valuable comments and suggestions. This research was substantially supported by the CRCG grant 335/017/0015 of the University of Hong Kong and a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. HKU 7169/98H). Upon completion of this paper, I became aware that similar work had been done independently by K.G. Yao and U. Böckenholt (1999).     

Logistic positive exponent family of models: Virtue of asymmetric item characteristic curves

The paper addresses and discusses whether the tradition of accepting point-symmetric item characteristic curves is justified by uncovering the inconsistent relationship between the difficulties of items and the order of maximum likelihood estimates of ability. This inconsistency is intrinsic in models that provide point-symmetric item characteristic curves, and in this paper focus is put on the normal ogive model for observation. It is also questioned if in the logistic model the sufficient statistic has forfeited the rationale that is appropriate to the psychological reality. It is observed that the logistic model can be interpreted as the case in which the inconsistency in ordering the maximum likelihood estimates is degenerated.The paper proposes a family of models, called the logistic positive exponent family, which provides asymmetric item chacteristic curves. A model in this family has a consistent principle in ordering the maximum likelihood estimates of ability. The family is divided into two subsets each of which has its own principle, and includes the logistic model as a transition from one principle to the other. Rationale and some illustrative examples are given.     

Exact person fit indexes for the rasch model for arbitrary alternatives

A new algorithm for obtaining exact person fit indexes for the Rasch model is introduced which realizes most powerful tests for a very general family of alternative hypotheses, including tests concerning DIF as well as model-deviating item correlations. The method is also used as a goodness-of-fit test for whole data sets where the item parameters are assumed to be known. For tests with 30 items at most, exact values are obtained, for longer tests a Monte Carlo-algorithm is proposed. Simulated examples and an empirical investigation demonstrate test power and applicability to item elimination.The author wishes to thank Elisabeth Ponocny-Seliger and the reviewers for many helpful comments. All exact goodness-of-fit tests proposed in this article are implemented in the menu-driven program T-Rasch 1.0 by Ponocny and Ponocny-Seliger (1999) which can be obtained from ProGAMMA (WWW: http://www.gamma.rug.nl) and also performs nonparametric tests.     

在内科临床中落实生物心理社会医学模式

社会心理因素与内科疾病的发生、发展和治疗效果关系密切,临床工作中忽视社会心理因素的作用可能导致严重后果。内科医生应积极拓展自身的知识技能,继而把对社会心理因素的重视落在实处,体现在病历中。完整的病史采集又需要加强医患沟通,如此才能真正发现和解决患者的社会心理问题。     

整体护理与新医学模式

整体护理作为当代护理的基本工作模式和护理学发展的基本趋势,是与生物心理社会医学模式的确立直接相联系的。在临床护理中,落实新医学模式,是推行整体护理所必需的。在整体护理中落实新医学模式应从转变护理人员观念、整体护理规范化、改变护理队伍的知识和技能结构、提供护士职业道德水平等方面做起。     

在新医学模式指导下预防碘缺乏病

碘缺乏病严重危害人类健康,是最大的、可预防的智力损伤因素。通过“社会动员”,推动防治碘缺乏病（ＩＤＤ）“轮子”运转,使我国消除ＩＤＤ事业有了巨大进步。目前存在的问题可能会影响到该事业的可持续发展。对此,提出一些建议。