人际间影响敏感性对中国消费者独特性需求的作用机制研究

以本土消费者为样本,采用实证研究方法就消费者的人际间影响敏感性与独特性需求之间的作用关系进行了分析。通过分析发现,从总体来看本土消费者对人际间影响所持有的敏感性对独特性需求产生了促进作用,这种因果关系在一定程度上解释了中国消费者在消费过程中所体现出的从众、攀比、好面子等独特现象的产生机理。     

The weighted jackknife for ratio estimation

Using the idea of impirical influence function, Hinkley (1977), the weighted jackknife technique is extended to ratio estimation. A weighted jackknife variance estimator for the ratio estimator is developed. Using the prediction theory approach, the properties of the weighted jackknifed variance estimator are examined. The implications of the failures of regression model on the behaviour of the weighted jackknifed variance estimator, for ratio estimation, are also studied.     

由日本动漫在中国的兴盛引发的思考

随着现代传媒技术的发展,动漫作为一种新兴的产业文化正日益蓬勃地发展。日本动漫以其制作精良、形象生动的特点占据了中国大部分的动漫市场,吸引了众多的青少年,而借助动漫,日本文化也在潜移默化中灌输给了青少年。文章试图分析日本动漫在中国的传播现状以及对中国的影响,从而提出面对日本动漫的冲击,中国动漫界应对的措施。     

巴洛克文学的多元文化价值及其影响场域

巴洛克文学曾受到文学批评史的不公正对待已是不争的事实。可是文学史的发展轨迹最终表明巴洛克文学具有多元文化价值、强大的生命力和不容忽视的影响场域。巴洛克文学的多元文化价值表现在：其一,生动再现17世纪欧洲各国的社会生活现实;其二,体现多元化的审美文化追求。巴洛克文学的影响场域表现为后世作家对其思想和艺术手法的借鉴、移植和化用,虽然亦存在着难以融合的断裂感和新异感。另外,这种影响还体现为一种追新逐异、兼收并蓄的＂巴洛克精神＂的广泛渗透。     

Factors That May Influence Parent Treatment Decision Making for Young Children with Autism Spectrum Disorder

ABSTRACT

The number of interventions available for children with autism spectrum disorder (ASD) has expanded greatly in recent years, although relatively little is known about the factors that influence family caregivers as they make treatment decisions for their children. This study involved a statewide survey of parents of young children with ASD to examine the relative weights of the factors that influenced their treatment decisions. Results suggested that caregivers rely on their own intuition for much decision making, although selected professionals are also influential. Implications for professionals working with children with ASD and their families are discussed.     

The Collapsing Choice Theory: Dissociating Choice and Judgment in Decision Making

Decision making theory in general, and mental models in particular, associate judgment and choice. Decision choice follows probability estimates and errors in choice derive mainly from errors in judgment. In the studies reported here we use the Monty Hall dilemma to illustrate that judgment and choice do not always go together, and that such a dissociation can lead to better decision-making. Specifically, we demonstrate that in certain decision problems, exceeding working memory limitations can actually improve decision choice. We show across four experiments that increasing the number of choice alternatives forces people to collapse choices together, resulting in better decision-making. While choice performance improves, probability judgments do not change, thus demonstrating an important dissociation between choice and probability judgments. We propose the Collapsing Choice Theory (CCT) which explains how working memory capacity, probability estimation, choice alternatives, judgment, and regret all interact and effect decision quality.      

Asymmetries in Information Processing in a Decision Theory Framework

Research in psychology suggests that some individuals are more sensitive to positive than to negative information while others are more sensitive to negative rather than positive information. I take these cognitive positive–negative asymmetries in information processing to a Bayesian decision-theory model and explore its consequences in terms of decisions and payoffs. I show that in monotone decision problems economic agents with more positive-responsive information structures are always better off, ex ante, when they face problems where payoffs are relatively more sensitive to the action chosen when the state of nature is favorable.      

Unwanted sexual experiences and sexual risks in gay and bisexual men: Associations among revictimization,substance use,and psychiatric symptoms

The data set of 2,182 gay/bisexual men's month‐long sexual diaries collected by the United Kingdom Socio‐sexual Investigations of Gay Men and Aids (Project SIGMA) was used to analyse the extent to which acts of anal intercourse (AI) are distributed among gay men, using the Lorenz/Gini methodology for measuring concentration. Most individuals (60%) who engage in AI do so only once or twice a month, but there is a long tail of those who do it much more. In terms of the amount of AI acts, one tenth of the individuals are performing half of the acts of AI. The Gini coefficient of concentration is high (0.55). Factors most affecting rates and concentration of risk behaviour include relationship status, HIV sero‐status and concordant/discordant partner status.     

Multiple deletion measures and conditional influence in regression model

The joint effect of the deletion of the ith and jih cases is given by Gray and Ling (1984), they discussed the influence measures for influential subsets in linear regression analysis. The present paper is concerned with multiple sets of deletion measures in the linear regression model. In particular we are interested in the effects of the jointly and conditional influence analysis for the detection of two influential subsets.     

Diagnostics for elliptical linear mixed models with first-order autoregressive errors

For longitudinal time series data, linear mixed models that contain both random effects across individuals and first-order autoregressive errors within individuals may be appropriate. Some statistical diagnostics based on the models under a proposed elliptical error structure are developed in this work. It is well known that the class of elliptical distributions offers a more flexible framework for modelling since it contains both light- and heavy-tailed distributions. Iterative procedures for the maximum-likelihood estimates of the model parameters are presented. Score tests for the presence of autocorrelation and the homogeneity of autocorrelation coefficients among individuals are constructed. The properties of test statistics are investigated through Monte Carlo simulations. The local influence method for the models is also given. The analysed results of a real data set illustrate the values of the models and diagnostic statistics.