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.     

学做服务工：中国都市青年、职业学校和新阶层的形成

中国职业学校学生的命运究竟如何？本文根据南京市两所职业学校为期一年（2007-2008年）的民族志研究,借由韦伯的分析路径,描述了职业学校学生学习生活以及最终由半技术工人进入新型服务经济领域的过程。研究表明,在今天的中国城市中,职业学校是一个产生新社会阶层的优选场所。首先,职业学校从结构和意识层面上生产一个独立的年轻人阶层群体;其次,职业学校打造的相似学生背景和共同生活空间有助于催生一种新的社会阶层和文化;再次,职业学校构建的新文化积极作用于学生的选择和生活方式,促使他们流向服务行业,成为半技术工人。总之,职业学校学生正处于一个新社会阶层初级阶段：共享着相似的生活方式、生活机遇、市场地位和有限的社会流动。     

Combining information from multiple surveys for assessing health disparities

Despite advances in public health practice and medical technology, the disparities in health among the various racial/ethnic and socioeconomic groups remain a concern which has prompted the Department of Human and Health Services to designate the elimination of disparities in health as an overarching goal of Healthy People 2010. To assess the progress towards this goal, suitable measures are needed at the population level that can be tracked over time; Statistical inferential procedures have to be developed for these population level measures; and the data sources have to be identified to allow for such inferences to be conducted. Popular data sources for health disparities research are large surveys such the National Health and Interview Survey (NHIS) or the Behavior Risk Factor Surveillance System (BRFSS). The self-report disease status collected in these surveys may be inaccurate and the errors may be correlated with variables used in defining the groups. This article uses the National Health and Nutritional Examination Survey (NHANES) 99-00 to assess the extent of error in the self-report disease status; uses a Bayesian framework develop corrections for the self-report disease status in the National Health Interview Survey (NHIS) 99-00; and compares inferences about various measures of health disparities, with and without correcting for measurement error. The methodology is illustrated using the disease outcome hypertension, a common risk factor for cardiovascular disease. JEL classification C1 (C11, C13, C15), C4 (C42) and I3 (I31, I38)     

Value of and Interaction between Production Postponement and Information Sharing Strategies for Supply Chain Firms

We analyze the value of and interaction between production postponement and information sharing, which are two distinct strategies to reduce manufacturers’ uncertainty about demand. In both single‐level and two‐level supply chains, from the manufacturer's perspective, while information sharing is always valuable, production postponement can sometimes be detrimental. Furthermore, the value of production postponement is not merely driven by savings in inventory holding cost as postponement enables the manufacturer to avoid both excess and shortfall in production. We find that production postponement and information sharing strategies may substitute, complement, or conflict with each other, depending on the extent of the increase in the unit production cost when production is postponed. In a two‐level supply chain, from the retailer's perspective, information sharing and production postponement can be beneficial or detrimental. When information sharing is beneficial to the retailer, the retailer always shares her demand information with the manufacturer voluntarily. In addition, this voluntary information sharing is truthful because inflated or deflated demand information hurts the retailer through a higher wholesale price or a stock‐out. However, the retailer never shares her demand information voluntarily if the manufacturer has already adopted production postponement because production postponement and information sharing strategies always conflict with each other. Even when the retailer does not benefit from information sharing, we show that the manufacturer can always design an incentive mechanism to induce the retailer to share the demand information, irrespective of whether the manufacturer has already implemented production postponement or not. The above findings underscore the need for a careful assessment of demand uncertainty‐reduction strategies before the supply chain players embark upon them.     

写作教学与创造性思维的培养

分析写作和创造性思维的相互促进的关系，结合实际探讨怎样通过写作教学提高学生的写作能力和思维创新能力。     

Impact of Information Systems (IS) Steering Committees on IS Planning*

One of the most efficient ways to manage the information systems function is to introduce steering committees. It has been suggested that one of the foremost benefits of a steering committee is that it can improve the information systems planning efforts of an organization. However, there is very little empirical evidence in the literature that deals with how such committees affect planning. This study investigates the impact of steering committees on three phases of information systems planning: strategic planning, systems planning, and implementation of planning. The greatest impact of steering committees appears to be the strategic planning phase, while a lesser effect is observed in the systems planning and implementation of planning phases.     

Combining information from multiple surveys for assessing health disparities

Despite advances in public health practice and medical technology, the disparities in health among the various racial/ethnic and socioeconomic groups remain a concern which has prompted the Department of Human and Health Services to designate the elimination of disparities in health as an overarching goal of Healthy People 2010. To assess the progress towards this goal, suitable measures are needed at the population level that can be tracked over time; Statistical inferential procedures have to be developed for these population level measures; and the data sources have to be identified to allow for such inferences to be conducted. Popular data sources for health disparities research are large surveys such the National Health and Interview Survey (NHIS) or the Behavior Risk Factor Surveillance System (BRFSS). The self-report disease status collected in these surveys may be inaccurate and the errors may be correlated with variables used in defining the groups. This article uses the National Health and Nutritional Examination Survey (NHANES) 99-00 to assess the extent of error in the self-report disease status; uses a Bayesian framework develop corrections for the self-report disease status in the National Health Interview Survey (NHIS) 99-00; and compares inferences about various measures of health disparities, with and without correcting for measurement error. The methodology is illustrated using the disease outcome hypertension, a common risk factor for cardiovascular disease.     

The Effect of Question Framing and Response Options on the Relationship between Racial Attitudes and Beliefs about Genes as Causes of Behavior

Prior research suggests that the attribution of individual and group differences to genetic causes is correlated with prejudiced attitudes toward minority groups. Our study suggests that these findings may be due to the wording of the questions and to the choice of response options. Using a series of vignettes in an online survey, we find a relationship between racial attitudes and genetic attributions when respondents are asked to make causal attributions of differences between racial groups. However, when they are asked to make causal attributions for characteristics shown by individuals, no such relationship is found. The response scale used appears to make less, if any, difference in the results. These findings indicate that the way questions about genetic causation of behavior are framed makes a significant contribution to the answers obtained because it significantly changes the meaning of the questions. We argue that such framing needs to be carefully attended to, not only in posing research questions but also in discourse about genetics more generally.     

全球化背景下云南多样性民族文化的碰撞与发展

文化多样性对人类来讲就像生物多样性对维持生物平衡那样必不可少,它是人类持续和谐发展的根本保证.云南是一个多民族的边疆省份,民族的多样性决定了其文化的多样性.经济全球化的发展为云南各民族不同文化之间的交流和交融提供了新的历史机遇,同时也加剧了各民族文化之间的碰撞.在此背景下,我们必须努力做到"文化自觉",尊重文化个性,加强文化的调适,推进文化整合,这样才能实现保护、传承和发展云南民族文化多样性的目标.     

Multiple imputation using multivariate gh transformations

Multiple imputation has emerged as a popular approach to handling data sets with missing values. For incomplete continuous variables, imputations are usually produced using multivariate normal models. However, this approach might be problematic for variables with a strong non-normal shape, as it would generate imputations incoherent with actual distributions and thus lead to incorrect inferences. For non-normal data, we consider a multivariate extension of Tukey's gh distribution/transformation [38] to accommodate skewness and/or kurtosis and capture the correlation among the variables. We propose an algorithm to fit the incomplete data with the model and generate imputations. We apply the method to a national data set for hospital performance on several standard quality measures, which are highly skewed to the left and substantially correlated with each other. We use Monte Carlo studies to assess the performance of the proposed approach. We discuss possible generalizations and give some advices to practitioners on how to handle non-normal incomplete data.