Generating synthetic data to produce public-use microdata for small geographic areas based on complex sample survey data with application to the National Health Interview Survey

Small area statistics obtained from sample survey data provide a critical source of information used to study health, economic, and sociological trends. However, most large-scale sample surveys are not designed for the purpose of producing small area statistics. Moreover, data disseminators are prevented from releasing public-use microdata for small geographic areas for disclosure reasons; thus, limiting the utility of the data they collect. This research evaluates a synthetic data method, intended for data disseminators, for releasing public-use microdata for small geographic areas based on complex sample survey data. The method replaces all observed survey values with synthetic (or imputed) values generated from a hierarchical Bayesian model that explicitly accounts for complex sample design features, including stratification, clustering, and sampling weights. The method is applied to restricted microdata from the National Health Interview Survey and synthetic data are generated for both sampled and non-sampled small areas. The analytic validity of the resulting small area inferences is assessed by direct comparison with the actual data, a simulation study, and a cross-validation study.     

All pairwise comparisons of exponential location parameters under type i censoring — equal scale parameter case

In this paper, procedures for all pairwise comparisons of location parameters of negative exponential populations are developed when the common scale parameter is known or unknown using large sample distributional approximations of the relevant random variables. The small sample performance of these procedures are then examined using Monte Carlo simulation.     

众数测算的一种新方法及其应用

针对传统众数估计值会因为组距的改变而不稳定,在已有的半极差(样本)众数估计方法上,提出多比例极差(样本)众数估计新方法。模拟研究显示,相对于半极差(样本)众数估计方法,该方法估计结果更稳定、准确。在实证分析中,基于2014、2015年国家一体化住户调查数据,使用新方法计算了新疆兵团居民人均可支配收入众数。结果表明,众数可以作为居民人均可支配收入平均数、中位数的有益补充,众数在政府统计中的推广及应用具有一定的可行性与必要性。     

多代合居模式下的卫浴空间通用设计

老年人、青年人、儿童多代合居的家庭,因生活方式的差异致使传统的卫浴空间设计显现出诸多问题。在空间规划、设施配置、氛围营造三个方面引入通用设计理念,合理设计卫浴空间使合居家庭的生活更加融洽。     

自动化立体仓库中出入库任务顺序与出库位置选择集成优化研究

具有多个出口的自动化立体仓库系统是一种将存储和分拣相结合的新型仓储技术,其最典型的特征是在货架底层有很多个出库位置以供取货人员分拣。研究此系统中出入库任务排序与出口选择的集成优化问题,以最小化堆垛机完成所有任务的移动距离为目标,将此问题转化为一个混合整数规划模型。根据问题的特点设计了两阶段启发式算法求解此问题,数值结果表明设计的算法能在较短时间内给出近似最优解,同时与企业常用的先到先服务方法相比,该算法可以缩短超过20%的移动距离。     

公司治理对会计信息披露质量影响 ——基于我国生物医药业上市公司的实证研究

会计信息披露是企业向信息使用者揭示和反映企业价值运动,高质量的信息披露可以降低信息不对称程度,使投资者能更正确地做出判断.以生物医药业上市公司为例,采用Logistic回归分析方法,系统研究公司治理与会计信息的披露质量之间的关系,发现公司治理中的董事会规模、独立董事比例和监事会规模的提高会使得会计信息披露质量得到提高,董事会会议次数与会计信息披露质量显著负相关.     

基于序化机理的稳健型股票价值投资决策——一个研究框架

面对资本市场风险加剧的现实背景,以"公司经营业绩与股票市场业绩一致趋优"为稳健型投资的核心要素,立足于区间数据表示、会计信息度量两个关键要素,开展稳健型股票价值投资的多准则决策建模研究。面向稳健型投资决策目标,提出满足"稳健性""局部性""全局性"3个特性的序化机理,围绕关键特征选择、特征评价、全序化建模的主体脉络建立系统性多准则决策方法,进而构建"稳健型股票价值投资决策"的研究框架。     

我国环境多元治理模式法律保障机制探究

未清晰地认识和定位政府、企业、社会公众三者的关系,未处理好三者的分工与衔接,是造成我国环境多元治理模式难以落实的关键问题。究其主要原因在于过分依赖传统政府管制模式的路径,以致政府在环境治理中起主导作用而轻视企业、社会公众作为治理主体的力量,导致其他治理主体参与环境治理法律机制的缺失。比较分析三者存在的障碍,提出落实环境多元治理模式法律保障的建议,从而构建起三者相互协作、共同治理环境的新局面。     

Collective versus Individual Effects in Survival Analysis of Multiple Failures

In survival analysis, we sometimes encounter data with multiple censored outcomes. Under certain scenarios, partial or even all covariates have ‘similar’ relative risks on the multiple outcomes in the Cox regression analysis. The similarity in covariate effects can be quantified using the proportionality of regression coefficients. Identifying the proportionality structure, or equivalently whether covariates have individual or collective effects, may have important scientific implications. In addition, it can lead to a smaller set of unknown parameters, which in turn results in more accurate estimation. In this article, we develop a novel approach for identifying the proportionality structure. Simulation shows the satisfactory performance of the proposed approach and its advantage over estimation under no assumed structure. We analyse three datasets to demonstrate the practical application of the proposed approach.     

A Rejection Principle for Sequential Tests of Multiple Hypotheses Controlling Familywise Error Rates

We present a unifying approach to multiple testing procedures for sequential (or streaming) data by giving sufficient conditions for a sequential multiple testing procedure to control the familywise error rate (FWER). Together, we call these conditions a ‘rejection principle for sequential tests’, which we then apply to some existing sequential multiple testing procedures to give simplified understanding of their FWER control. Next, the principle is applied to derive two new sequential multiple testing procedures with provable FWER control, one for testing hypotheses in order and another for closed testing. Examples of these new procedures are given by applying them to a chromosome aberration data set and finding the maximum safe dose of a treatment.