Estimating the parameters of the latent population distribution

Under consideration is a test battery of binary items. The responses ofn individuals are assumed to follow a Rasch model. It is further assumed that the latent individual parameters are distributed within a given population in accordance with a normal distribution. Methods are then considered for estimating the mean and variance of this latent population distribution. Also considered are methods for checking whether a normal population distribution fits the data. The developed methods are applied to data from an achievement test and from an attitude test.     

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.     

西方心育教学模式评介

本文探讨了心育与心育教学模式的意义 ;着重介绍了西方几种有代表性的心育教学模式 ,即布鲁纳的发现教学法、威廉姆斯的创造与情意教学模式、开放教室的教学模式与勒温的敏感性训练等 ;并与传统教学模式相比较 ,分析了西方心育教学模式的主要特征     

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.     

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.     

A one-boundary drift-diffusion model for time to collision estimation in a simple driving task

ABSTRACT

Driving is a complex everyday task. Every year a huge number of driving accidents around the world causes serious physical and mental injuries and deaths. The correct estimation of the remaining time to reach the other vehicles on the road, known as time to collision (TTC), is an important factor to avoid accidents. In this study, we aimed to use a drift-diffusion model (DDM) to better understand the participants’ estimation of TTC in two driving experiments. Both experiments were the same, except that in one of them participants were asked to finish the experiment as fast as they could, while in the other experiment there was no time constraint. DDM fitted the data from all participants well in both experiments according to the chi-square goodness of fit criterion. Also, results showed that time pressure increases subjects’ estimated TTC, the rate of accumulation of sensory information and the response threshold.     

Maximum likelihood additivity analysis

A maximum likelihood estimation procedure was developed to fit unweighted and weighted additive models to conjoint data obtained by the categorical rating, the pair comparison or the directional ranking method. The scoring algorithm used to fit the models was found to be both reliable and efficient, and the program MAXADD is capable of handling up to 300 parameters to be estimated. Practical uses of the procedure are reported to demonstrate various advantages of the procedure as a statistical method.The research reported here was supported by Grant A6394 to the author from the Natural Sciences and Engineering Research Council of Canada. Portions of this research were presented at the Psychometric Society meeting in Iowa City, Iowa, in May, 1980.Thanks are due to Jim Ramsay, Justine Sergent and anonymous reviewers for their helpful comments.Two MAXADD programs which perform the computations discussed in this paper may be obtained from the author.     

冠状动脉搭桥术后再狭窄研究的思考

冠状动脉搭桥术(CABG)是目前外科治疗冠心病的成熟、定型的手术方法,但术后再狭窄影响了病人的远期疗效,其研究也越来越受到人们重视。随着生物医学模式向生物心理社会医学模式的转变,研究者对CABG术后再狭窄也有了更深入的认识,更加注重整体性、动态化和系统最优化。试用系统论方法探讨CABG术后再狭窄的防治。