To buy or to sell: cultural differences in stock market decisions based on price trends

Four studies compared the stock market decisions of Canadians and Chinese. In two studies using simple stock market trends, compared with Chinese, Canadians were more willing to sell and less willing to buy falling stock. But when the stock price was rising, the opposite occurred: Canadians were more willing to buy and less willing to sell. A third study showed that for complex stock price trends, Canadians were strongly influenced by the most recent price trends: they tended to predict that recent trends would continue and made selling decisions without considering the rest of the trend patterns; whereas the Chinese made reversal predictions for the dominant trends and made decisions that took both recent and early trends into consideration. Study 4 replicated the finding with experienced individual investors. These findings are consistent with the previous literature on different lay theories of change held by Chinese and North Americans. Copyright © 2008 John Wiley & Sons, Ltd.     

Detecting and (Not) Dealing with Plagiarism in an Engineering Paper: Beyond CrossCheck—A Case Study

In papers in areas such as engineering and the physical sciences, figures, tables and formulae are the basic elements to communicate the authors’ core ideas, workings and results. As a computational text-matching tool, CrossCheck cannot work on these non-textual elements to detect plagiarism. Consequently, when comparing engineering or physical sciences papers, CrossCheck may return a low similarity index even when plagiarism has in fact taken place. A case of demonstrated plagiarism involving engineering papers with a low similarity index is discussed, and editor’s experiences and suggestions are given on how to tackle this problem. The case shows a lack of understanding of plagiarism by some authors or editors, and illustrates the difficulty of getting some editors and publishers to take appropriate action. Consequently, authors, journal editors, and reviewers, as well as research institutions all are duty-bound not only to recognize the differences between ethical and unethical behavior in order to protect a healthy research environment, and also to maintain consistent ethical publishing standards.     

高考数学试卷多维项目反应理论的分析及应用

高考数学学科试卷的试题综合性较强,一道试题通常考查多种能力属性,而基于单维性假设下的经典测量理论和传统的项目反应理论无法完成该种情形下试卷测量性能分析和考生作答表现分析.本文以MIRT理论为基础,使用CONQUEST软件为工具进行分析,可以获得试卷内部不同能力维度之间的相关以及考生不同维度的能力参数,为提升命题质量和改进教学提供了依据,表明MIRT具有很好的应用前景.由于MIRT理论的复杂性以至于目前分析软件的不足制约其进一步的深入应用,这是今后应该深入研究的问题.     

宗教视角下的南亚恐怖主义特征与反恐的若干思考

本文详细探究和分析了后冷战时代宗教在南亚地区恐怖主义泛滥背景下的特征,指出不同宗教间的冲突成为南亚恐怖主义最主要的特征,并分析了南亚恐怖组织的宗教背景,强调恐怖主义对南亚造成了巨大危害,加深了不同宗教间的仇视。最后,从南亚自身实际出发,提出加强不同宗教间的对话,消除彼此之间的不信任感和仇恨感是南亚地区反恐的重中之重。     

Bayesian Estimation of Categorical Dynamic Factor Models

Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations—the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model—to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with a categorical time series data set from an emotion study. To estimate the categorical dynamic factor models, a Bayesian method via Gibbs sampling is used. The results show that today's affect directly influences tomorrow's affect. The results are then validated by means of simulation studies. Differences between continuous and categorical dynamic factor models are examined.     

Structural Equation Modeling of Social Networks: Specification,Estimation, and Application

Psychologists are interested in whether friends and couples share similar personalities or not. However, no statistical models are readily available to test the association between personalities and social relations in the literature. In this study, we develop a statistical model for analyzing social network data with the latent personality traits as covariates. Because the model contains a measurement model for the latent traits and a structural model for the relationship between the network and latent traits, we discuss it under the general framework of structural equation modeling (SEM). In our model, the structural relation between the latent variable(s) and the outcome variable is no longer linear or generalized linear. To obtain model parameter estimates, we propose to use a two-stage maximum likelihood (ML) procedure. This modeling framework is evaluated through a simulation study under representative conditions that would be found in social network data. Its usefulness is then demonstrated through an empirical application to a college friendship network.     

Bayesian Inference for Growth Mixture Models with Latent Class Dependent Missing Data

Growth mixture models (GMMs) with nonignorable missing data have drawn increasing attention in research communities but have not been fully studied. The goal of this article is to propose and to evaluate a Bayesian method to estimate the GMMs with latent class dependent missing data. An extended GMM is first presented in which class probabilities depend on some observed explanatory variables and data missingness depends on both the explanatory variables and a latent class variable. A full Bayesian method is then proposed to estimate the model. Through the data augmentation method, conditional posterior distributions for all model parameters and missing data are obtained. A Gibbs sampling procedure is then used to generate Markov chains of model parameters for statistical inference. The application of the model and the method is first demonstrated through the analysis of mathematical ability growth data from the National Longitudinal Survey of Youth 1997 (Bureau of Labor Statistics, U.S. Department of Labor, 1997). A simulation study considering 3 main factors (the sample size, the class probability, and the missing data mechanism) is then conducted and the results show that the proposed Bayesian estimation approach performs very well under the studied conditions. Finally, some implications of this study, including the misspecified missingness mechanism, the sample size, the sensitivity of the model, the number of latent classes, the model comparison, and the future directions of the approach, are discussed.     

从客观决定性到意志自由——论行动哲学研究的方法论变革

如果说心灵哲学是当代西方学术界的“第一哲学”,那么,以“客观决定性VS．意志自由”为核心问题的行动哲学研究,则是这种哲学研究在当今最重要的组成部分和基本发展趋势,因而只有在研究客观决定性和意志自由的相互关系方面取得了根本性突破,行动哲学和心灵哲学研究才有可能取得实质性进展。不过,由于绝大多数研究者都没有通过对惟理智主义研究方法论的深刻批判反思而达到方法论的自觉,所以,只有真正实现了对由基本倾向、思维方式和研究模式构成的研究方法论的彻底变革,这样的突破才是可能的;本文认为,以社会个体生成论彻底扬弃和取代基于抽象个体的预成论,是实现这种变革的富有建设性意义的学术理路。     

摩托车驾驶员驾驶行为、人格、交通安全态度与事故的关系研究

本研究采用摩托车驾驶员驾驶行为问卷、中国人人格量表、感觉寻求量表和交通安全态度问卷,对800名摩托车驾驶员的驾驶行为、人格、交通安全态度与摩托车交通事故的关系进行了探讨.结果表明:摩托车驾驶员的人格、交通安全态度对驾驶行为有直接影响;驾驶行为、交通安全态度对事故有直接的影响;摩托车驾驶员的人格和交通安全态度也可通过驾驶行为间接影响事故.