群体决策支持系统的模型库研究

通过对传统模型及模型库的分析,指出其在网络环境下具有难以实现共享的不足.从模型在网络上共享及其软件实现的角度,在分布式网络数据库环境下,利用分布式网络数据库技术,设计了模型库的结构和机理;提出了模型库的构造方法;对模型库的内部控制方式进行了设计;提出了模型库对群体决策的支持方式;客户端的决策成员对模型库的共享与访问方法.     

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.     

Examples of the use of an equivalence theorem in constructing optimum experimental designs for random-effects nonlinear regression models

The problem considered is that of finding an optimum measurement schedule to estimate population parameters in a nonlinear model when the patient effects are random. The paper presents examples of the use of sensitivity functions, derived from the General Equivalence Theorem for D-optimality, in the construction of optimum population designs for such schedules. With independent observations, the theorem applies to the potential inclusion of a single observation. However, in population designs the observations are correlated and the theorem applies to the inclusion of an additional measurement schedule. In one example, three groups of patients of differing size are subject to distinct schedules. Numerical, as opposed to analytical, calculation of the sensitivity function is advocated. The required covariances of the observations are found by simulation.     

Non-ignorable missing covariate data in survival analysis: a case-study of an International Breast Cancer Study Group trial

Summary.  Non-ignorable missing data, a serious problem in both clinical trials and observational studies, can lead to biased inferences. Quality-of-life measures have become increasingly popular in clinical trials. However, these measures are often incompletely observed, and investigators may suspect that missing quality-of-life data are likely to be non-ignorable. Although several recent references have addressed missing covariates in survival analysis, they all required the assumption that missingness is at random or that all covariates are discrete. We present a method for estimating the parameters in the Cox proportional hazards model when missing covariates may be non-ignorable and continuous or discrete. Our method is useful in reducing the bias and improving efficiency in the presence of missing data. The methodology clearly specifies assumptions about the missing data mechanism and, through sensitivity analysis, helps investigators to understand the potential effect of missing data on study results.     

Statistical and Combinatorial Aspects of Comparative Genomics*

Abstract. This document presents a survey of the statistical and combinatorial aspects of four areas of comparative genomics: gene order based measures of evolutionary distances between species, construction of phylogenetic trees, detection of horizontal transfer of genes, and detection of ancient whole genome duplications.     

On Optimality of Bayesian Wavelet Estimators

Abstract.  We investigate the asymptotic optimality of several Bayesian wavelet estimators, namely, posterior mean, posterior median and Bayes Factor, where the prior imposed on wavelet coefficients is a mixture of a mass function at zero and a Gaussian density. We show that in terms of the mean squared error, for the properly chosen hyperparameters of the prior, all the three resulting Bayesian wavelet estimators achieve optimal minimax rates within any prescribed Besov space     for p  ≥ 2. For 1 ≤  p  < 2, the Bayes Factor is still optimal for (2 s +2)/(2 s +1) ≤  p  < 2 and always outperforms the posterior mean and the posterior median that can achieve only the best possible rates for linear estimators in this case.     

Assessing goodness-of-fit of categorical regression models based on case-control data

Demonstrated equivalence between a categorical regression model based on case‐control data and an I‐sample semiparametric selection bias model leads to a new goodness‐of‐fit test. The proposed test statistic is an extension of an existing Kolmogorov–Smirnov‐type statistic and is the weighted average of the absolute differences between two estimated distribution functions in each response category. The paper establishes an optimal property for the maximum semiparametric likelihood estimator of the parameters in the I‐sample semiparametric selection bias model. It also presents a bootstrap procedure, some simulation results and an analysis of two real datasets.     

绿色供应链管理动力/压力影响模型实证研究

文章借鉴国外文献及国内环保专家的意见设计问卷进行调研,通过因子分析识别出中国制造企业绿色供应链管理的压力/动力和实践的主要因子.对因子进行相关分析和回归分析,根据数据结合国内外相关情况探讨动力/压力是如何影响绿色供应链管理实践,提出中国制造企业绿色供应链管理的动力/压力影响模型.     

影响我国产业内贸易发展的因素及其对策思考

二战后,产业内贸易发展迅速,发展中国家若要真正有效地参与国际经济大循环,加快本国经济发展,就必须加入到产业内贸易的大潮中去。我国产业内贸易应从发展现状入手,着重对影响我国产业内贸易发展的产业结构因素、产业组织结构因素和政策因素制定相关对策,以不断提高我国外贸竞争力。     

地力山土族生计方式与家庭经济结构

地力山是甘南藏族自治州卓尼县杓哇土族乡的一个纯土族自然村。由于特定的历史、自然和社会原因,形成了以农为主牧业为辅的传统生计方式。随着时代的变化,兼事务工成为了传统生计方式的补充。在地力山土族家庭经济过程中,生计方式支配着资源要素的投入方向,而资源要素在不同方向上的配置最终构成其家庭经济的各个形态,形态之间以及具体形态内部存在的动态性,为其进一步调整提供了内在条件。