A Graphical Tool for Interpreting Regression Coefficients of Trinomial Logit Models

Multinomial logit (also termed multi-logit) models permit the analysis of the statistical relation between a categorical response variable and a set of explicative variables (called covariates or regressors). Although multinomial logit is widely used in both the social and economic sciences, the interpretation of regression coefficients may be tricky, as the effect of covariates on the probability distribution of the response variable is nonconstant and difficult to quantify. The ternary plots illustrated in this article aim at facilitating the interpretation of regression coefficients and permit the effect of covariates (either singularly or jointly considered) on the probability distribution of the dependent variable to be quantified. Ternary plots can be drawn both for ordered and for unordered categorical dependent variables, when the number of possible outcomes equals three (trinomial response variable); these plots allow not only to represent the covariate effects over the whole parameter space of the dependent variable but also to compare the covariate effects of any given individual profile. The method is illustrated and discussed through analysis of a dataset concerning the transition of master’s graduates of the University of Trento (Italy) from university to employment.     

工业设计专业数字化设计类课程体系建设的思考

针对数字化技术对工业设计的巨大影响 ,提出了工业设计专业数字化设计类课程体系的框架和对一些课程设置及教学方法的设想     

黑龙江省老工业基地改造策略研究--与俄罗斯科技合作的视角

策略的选择关乎黑龙江省老工业基地改造的质量和效率,而老工业基地改造的关键在于运用高新技术促进产业结构的调整和产业技术的升级。俄罗斯是一个极具科技实力和潜力的国家,黑龙江省有着与俄科技合作的地缘优势、文化优势、人才优势以及历史和现实工作基础。因此,可以从与俄科技合作的视角探讨黑龙江省老工业基地改造的策略。应从战略高度审视利用与俄科技合作改造黑龙江省老工业基地,提升核心竞争力,走内涵式发展道路;重视软环境建设;分层规划;分组实施;重点支持若干领域,带动整体发展。     

美国"新经济"对中国的启示

美国“新经济”是以现代高新技术为基础的知识密集型经济,具有与传统经济相比的新的特征,带来了美国经济的繁荣和发展。在面临全球经济一体化的形势下,美国新经济对促进中国经济的发展和提高国际竞争力都有一定的借鉴和启发意义。     

善是什么

善恶观念的产生要从物质实践出发来解释。对什么是善的问题 ,西方伦理学家们依据自己不同的研究方法 ,各抒己见 ,这些观点有其合理性 ,同时也存在着不可避免的缺陷 ,追问善的问题 ,离不开对善恶关系的探讨 ,善恶是相对的 ,同时也存在着客观的评价标准。考察善是什么 ,必须将动机与效果统一起来才能把握     

面对"入世"挑战,加快农业产业化经营

加入世贸组织给中国农业带来了发展机遇,同时也带来严峻的挑战。中国农业必须立足优势,培育和发展主导产业;加快龙头企业的培育和建设,发展农村专业合作经济组织;加强科技投入,倡导农业科技创新;充分利用WTO农业规则,保护我国农业,加快农业产业化,迎接“入世”挑战。     

国际贸易和直接投资:基于产业经济学的分析

传统的国际贸易和投资理论习惯于从国家级的宏观水平上,对一个国家的总体贸易流和投资活动作出解释。产业经济学对贸易流和投资的分析却有自己的传统,其特点是在产业级的微观水平上进行分析。在经济全球化条件下,产业经济学国际化研究的一个重要的主题是揭示来自外国的竞争对本国市场绩效的影响和作用机制,主要利用产业层面的模型去揭示市场结构对进出口和外国直接投资的影响。这种方法把市场结构的构成要素(规模经济、产品差异度、交易成本等)作为决定贸易流和外国直接投资的动力机制。在ＷＴＯ的规则下,这种产业经济学国际化的研究对指导中国的对外开放实践和国内竞争政策的制订具有重要的理论和现实意义。     

A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data

Estimated associations between an outcome variable and misclassified covariates tend to be biased when the methods of estimation that ignore the classification error are applied. Available methods to account for misclassification often require the use of a validation sample (i.e. a gold standard). In practice, however, such a gold standard may be unavailable or impractical. We propose a Bayesian approach to adjust for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov Chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. A simulated numerical example and a real clinical example are given to illustrate the proposed approach. Our results suggest that the estimated log odds of inpatient care and the corresponding standard deviation are much larger in our proposed method compared with the models ignoring misclassification. Ignoring misclassification produces downwardly biased estimates and underestimate uncertainty.     

面孔认知中表情的印象操作的有效性

运用促进面孔记忆新的处理策略“表情的印象操作”，研究在笑脸中包含着怎样的信息。研究发现，与平静表情的面孔相比，笑脸是更具优势的表情，在笑脸的表情之中包含着更多促进面孔记忆的信息。     

A Note on the Role of the Propensity Score for Estimating Average Treatment Effects

Hahn [Hahn, J. (1998). On the role of the propensity score in efficient semiparametric estimation of average treatment effects. Econometrica 66:315-331] derived the semiparametric efficiency bounds for estimating the average treatment effect (ATE) and the average treatment effect on the treated (ATET). The variance of ATET depends on whether the propensity score is known or unknown. Hahn attributes this to “dimension reduction.” In this paper, an alternative explanation is given: Knowledge of the propensity score improves upon the estimation of the distribution of the confounding variables.