Multivariate regression analysis of panel data with binary outcomes applied to unemployment data

Summary  In panel studies binary outcome measures together with time stationary and time varying explanatory variables are collected over time on the same individual. Therefore, a regression analysis for this type of data must allow for the correlation among the outcomes of an individual. The multivariate probit model of Ashford and Sowden (1970) was the first regression model for multivariate binary responses. However, a likelihood analysis of the multivariate probit model with general correlation structure for higher dimensions is intractable due to the maximization over high dimensional integrals thus severely restricting ist applicability so far. Czado (1996) developed a Markov Chain Monte Carlo (MCMC) algorithm to overcome this difficulty. In this paper we present an application of this algorithm to unemployment data from the Panel Study of Income Dynamics involving 11 waves of the panel study. In addition we adapt Bayesian model checking techniques based on the posterior predictive distribution (see for example Gelman et al. (1996)) for the multivariate probit model. These help to identify mean and correlation specification which fit the data well. C. Czado was supported by research grant OGP0089858 of the Natural Sciences and Engineering Research Council of Canada.     

Diagnostic checks for discrete data regression models using posterior predictive simulations

Model checking with discrete data regressions can be difficult because the usual methods such as residual plots have complicated reference distributions that depend on the parameters in the model. Posterior predictive checks have been proposed as a Bayesian way to average the results of goodness-of-fit tests in the presence of uncertainty in estimation of the parameters. We try this approach using a variety of discrepancy variables for generalized linear models fitted to a historical data set on behavioural learning. We then discuss the general applicability of our findings in the context of a recent applied example on which we have worked. We find that the following discrepancy variables work well, in the sense of being easy to interpret and sensitive to important model failures: structured displays of the entire data set, general discrepancy variables based on plots of binned or smoothed residuals versus predictors and specific discrepancy variables created on the basis of the particular concerns arising in an application. Plots of binned residuals are especially easy to use because their predictive distributions under the model are sufficiently simple that model checks can often be made implicitly. The following discrepancy variables did not work well: scatterplots of latent residuals defined from an underlying continuous model and quantile–quantile plots of these residuals.     

基于战略杠杆原理的广西工业企业创新

战略杠杆能够实现“以少搏多”、“以弱胜强”,能为广西工业企业的快速成长与发展提供有效的途径。广西工业企业急需以全面系统的战略杠杆理论作为指导。我们在对战略杠杆原理及其与核心能力的关系进行系统分析的基础上,结合广西工业企业发展现状,阐述广西工业企业实施战略杠杆的现状及其得失原因,探讨以核心能力为基础的广西工业企业创新模型的对策,据此提出有益的建议。     

Alternative posterior consistency results in nonparametric binary regression using Gaussian process priors

We establish consistency of posterior distribution when a Gaussian process prior is used as a prior distribution for the unknown binary regression function. Specifically, we take the work of Ghosal and Roy [2006. Posterior consistency of Gaussian process prior for nonparametric binary regression. Ann. Statist. 34, 2413–2429] as our starting point, and then weaken their assumptions on the smoothness of the Gaussian process kernel while retaining a stronger yet applicable condition about design points. Furthermore, we extend their results to multi-dimensional covariates under a weaker smoothness condition on the Gaussian process. Finally, we study the extent to which posterior consistency can be achieved under a general model where, when additional hyperparameters in the covariance function of a Gaussian process are involved.     

高新技术行业动态联盟探析

动态联盟是企业合作的一种新模式 ,高新技术企业可以利用它抓住瞬息万变、稍纵即逝的市场机会。本文分析了动态联盟的特点 ,指出高新技术企业组建动态联盟的动因是为了快速响应市场机会。在此基础上 ,着重对高新技术企业动态联盟组建与管理中的几个关键要素进行了分析。     

加入WTO后我国外资银行准入法制的完善——以《巴塞尔核心原则》为视角

随着国际商贸的发展 ,国际贸易法也日趋完备 ,其中银行在国际商务活动中扮演着重要角色。加入世界贸易组织以后 ,中国将进一步开放金融市场。对外资金融机构准入法制的完善显得尤为重要 ,因此应研究并借鉴巴塞尔核心原则。     

中国古代王权稳固的基石——从《孝经》思想谈起

在中国古代社会特定的自然、人文环境下,本是规范家族内部行为的孝跃升为维护专制统治的政治理论武器。集中体现孝治思想的儒家著作——《孝经》,成为历代的治国经典。本文从《孝经》所指导的行为实践和所升华的核心价值两个层面,分析其如何有效发挥作用,进而成为稳固王权主义的坚强基石。     

现代大学核心竞争力的建设

大学作为高素质人才的培养基地,其核心竞争力的打造和提升对文化竞争力的提升意义重大。本文研究了大学核心竞争力在不同层次上的体现,提出了多种打造核心竞争力的方法与技术,并探讨了在当前形势下提升核心竞争力的保障措施。所提出的理论与方法紧密结合实际,对我国大学打造核心竞争力、实现跨越式发展具有较强的指导意义。     

幼儿教师视角下的有效园本教研特征——基于扎根理论的个案研究

摘 要：本研究为个案研究,基于扎根理论研究法,通过访谈12位来自福建省城市与农村的不同教龄的幼儿园园长与教师,探知他们认为有效促进其专业发展的园本教研应具备的核心特征。通过三级编码,67个初始编码,17个子范畴与6个核心范畴被发现,其中,幼儿教师视角下的有效园本教研的核心特征包括：建立共同愿景;支持与共享的领导;实践经验的梳理、分享、学习与运用;强调外部知识的移转;以问题为导向的反思型教研以及提供持续运作的支持。研究发现,园本教研中教与学的权力关系已开始转变;在运用外部知识中矛盾重重;重视结构性支持,忽视关系支持等园本教研现状。最后,研究者提出了针对性的建议。     

“微时代”高校社会主义核心价值观教育路径探究--微信对青年大学生认知和价值观的影响

在新媒体时代,微信极大地改变了人们生活、学习、工作方式,也深刻影响着大学生的生活方式和习惯。它是一把双刃剑,既为高校社会主义核心价值观教育带来了新的发展机遇,同时,又带来了一些风险和挑战。在微时代背景下,高校要进一步借力微信传播工具,搭建平台、创新内容和手段、建设队伍、加强监督,进一步增强社会主义核心价值观教育工作的针对性和实效性,加强社会主义核心价值观教育工作。