An interactive fuzzy satisficing method for multiobjective stochastic linear programming problems using chance constrained conditions

Two major approaches to deal with randomness or ambiguity involved in mathematical programming problems have been developed. They are stochastic programming approaches and fuzzy programming approaches. In this paper, we focus on multiobjective linear programming problems with random variable coefficients in objective functions and/or constraints. Using chance constrained programming techniques, the stochastic programming problems are transformed into deterministic ones. As a fusion of stochastic approaches and fuzzy ones, after determining the fuzzy goals of the decision maker, interactive fuzzy satisficing methods to derive a satisficing solution for the decision maker by updating the reference membership levels is presented. Copyright © 2003 John Wiley & Sons, Ltd.     

A caveat on the Savage–Dickey density ratio: The case of computing Bayes factors for regression parameters

The Savage–Dickey density ratio is a simple method for computing the Bayes factor for an equality constraint on one or more parameters of a statistical model. In regression analysis, this includes the important scenario of testing whether one or more of the covariates have an effect on the dependent variable. However, the Savage–Dickey ratio only provides the correct Bayes factor if the prior distribution of the nuisance parameters under the nested model is identical to the conditional prior under the full model given the equality constraint. This condition is violated for multiple regression models with a Jeffreys–Zellner–Siow prior, which is often used as a default prior in psychology. Besides linear regression models, the limitation of the Savage–Dickey ratio is especially relevant when analytical solutions for the Bayes factor are not available. This is the case for generalized linear models, non-linear models, or cognitive process models with regression extensions. As a remedy, the correct Bayes factor can be computed using a generalized version of the Savage–Dickey density ratio.     

Attachment Change in Emotionally Focused Couple Therapy and Sexual Satisfaction Outcomes in a Two-year Follow-up Study

Emotionally focused couple therapy (EFT) is an empirically validated attachment based approach to couple therapy. From an EFT perspective, sexual functioning is viewed within the context of an attachment bond, but sexual satisfaction in EFT has not been empirically tested. We examined self-reported sexual satisfaction across 24?months in a sample of 32 couples who received an average of 21 EFT sessions. We found that sexual satisfaction increased across six time points from pre to post therapy and across follow-up (6, 12, 18, and 24?months), and that decreases in attachment avoidance from pre to post therapy predicted increases in sexual satisfaction across time. These findings provide evidence that EFT may help couples improve their sexual satisfaction by reducing attachment avoidance in therapy.     

管理评价判断模型与策略获取

管理评价是在不确定情景中的一种多特征决策,非补偿策略是决策者所采用的主导判断模型。作为一种结构建模程序,策略捕捉可以建构包含决策标准及其权重的统计模型,获取决策内在过程和预测判断。多层线性模型能够方便地考察人内和人间变异,表征判断非线性结构,是分析策略捕捉数据的恰当方法。管理评价设计可以借鉴行为经济学和实验经济学的思路,实现对现实管理决策过程的抽象模拟。     

Capturing the interplay among within- and between-person processes using multilevel modeling techniques

Multilevel modeling is an excellent way to analyze nested or clustered data of the type commonly collected through investigations into the linkages between psychological functioning and relationship processes. This article describes two especially relevant applications of multilevel modeling. The first application, growth curve analysis, is already familiar to many researchers and involves modeling individuals’ change trajectories over time and relating the derived change parameters to person-level characteristics or phenomena. The purpose of this paper is to emphasize a second application, multilevel process analysis, which involves modeling within-subject characteristics other than change over a representation of time. Multilevel analysis of within-subject processes is particularly well-suited for hypotheses common to clinical psychology investigations, yet has received substantially less attention in the literature than its growth curve counterpart. Types of research questions and methodologies that can be addressed within the multilevel process analysis framework are described. Finally, aspects of multilevel process analysis are demonstrated with daily diary data collected from wives who reported on their marital happiness and depressed mood for 3 weeks.     

中国消费者价格容忍度的特点

运用多维线性模型,对我国消费者对不同产品价格涨落的容忍态度进行了研究。研究对象为26384名购买过各类产品的消费者。结果表明：（1）消费者对不同产品的价格容忍度不同,对日用消费品的价格容忍度较高,对耐用消费品的价格容忍度相对较低;（2）消费者的年龄和受教育程度对价格容忍度有负向的影响,消费者的年龄和受教育程度越高,对产品的价格容忍度越低;（3）男性消费者的价格容忍度高于女性消费者,女性消费者对价格较为敏感。     

超文本阅读绩效研究述评——认知的视角

网络不同于传统媒介的最大特点是以灵活的超文本形式呈现信息,超文本将关联的信息以网络状形式加以组织,读者可以通过链接从一个节点跳转到其他任何一个节点。本文回顾了超文本阅读的研究历程,指出目前这一领域研究存在的困境并试图寻找原因,在此基础上提出了今后研究的建议。     

The Importance of Community Context for Young Women’s Occupational Aspirations

The effects of community context on occupational aspirations are examined in a national sample of young women in high school in the USA in 1979 (n = 2,210). Multilevel statistical models indicate that young women living in counties with a lower divorce rate, a lower percentage of women working, and more people employed in the wholesale and retail industrial sector tended to be less likely to aspire to paid work than young women living in areas with a higher divorce rate, a higher percentage of women working, and fewer people employed in the wholesale and retail industrial sector. Community context does not affect the level of young women’s occupational aspirations as predicted by prior scholarship. An earlier version of this paper was presented at the 2006 Southern Sociological Society Annual Meetings. The author thanks John Reynolds, Patricia Yancey Martin, Irene Padavic, Robert Kunovich, Jennifer Keene, Mary Guy, and the editor and reviewers at Sex Roles for their helpful comments on previous drafts of this paper.     

儿童数字估计的表征模式与发展

探讨中国儿童数字估计的表征模式与发展趋势。包括两个实验,均采用数字线估计任务,实验一以92名幼儿园、一年级及二年级儿童为被试,考察其在0~100范围的数字估计,结果显示,幼儿园儿童在数字估计更多地采用对数表征,而一二年级的儿童在数字估计中更多地采用线性表征;实验二以86名一、三、五年级儿童为被试,考察其在0~1000范围的数字估计,结果显示,一年级儿童有一半采用对数表征,另一半采用线性表征,而三五年级儿童大多采用线性表征。中国儿童的数字估计表现出与美国儿童相同的发展模式,都是由不精确的对数表征逐步向精确的线性表征发展;人的数表征有多种形式,即使在同一年龄阶段,也会因任务难度的不同而选择不同的表征模式。中国儿童精确数字估计能力的出现要早于美国儿童。