Cumulative correspondence analysis of ordered categorical data from industrial experiments

Most studies of quality improvement deal with ordered categorical data from industrial experiments. Accounting for the ordering of such data plays an important role in effectively determining the optimal factor level of combination. This paper utilizes the correspondence analysis to develop a procedure to improve the ordered categorical response in a multifactor state system based on Taguchi's statistic. Users may find the proposed procedure in this paper to be attractive because we suggest a simple and also popular statistical tool for graphically identifying the really important factors and determining the levels to improve process quality. A case study for optimizing the polysilicon deposition process in a very large-scale integrated circuit is provided to demonstrate the effectiveness of the proposed procedure.     

中国农村公共服务评价体系研究

农村公共服务水平低下和不平衡是导致城乡差距日益扩大的重要影响因素之一。本文试图构建农村公共服务发展状况评价指标体系,并基于2006年的数据进行实证研究,给出了研究结果的进一步分析评价。     

中美石油安全水平对经济增长影响的对比研究——基于灰色关联分析

为科学地评价比较中美石油安全水平对经济增长的影响程度,文章采用主成分分析方法,选取采储比水平、储量接替率、消费弹性系数、原油价格波动系数、对外依存度和石油占一次能源消费比重等6个要素指标,构成一个新的石油安全指标评价体系,并利用灰色关联方法比较分析了不同时间段内中美两国的石油安全水平与经济增长之间的关联度,得出自21世纪以来,美国经济发展对石油安全水平的依赖程度要远大于中国的结论。     

制造业效率区域差异及其影响因素分析——基于中国省级面板数据的研究

制造业的发展关系到第二产业乃至整个国民经济的发展,制造业的增长是中国工业经济增长的主导力量。本文运用数据包络分析法,测度了制造业各行业及中国各省制造业效率情况,然后利用中国省级制造业效率指标以及专利申请、地区经济发展水平等制造业效率影响因素的外延数据构成面板数据（Panel Data）建立模型。通过实证分析得出：地区经济的发展有利于制造业效率的提升。专利申请与制造业效率呈负相关。     

Nonparametric and semiparametric estimation of the three way receiver operating characteristic surface

In many situations the diagnostic decision is not limited to a binary choice. Binary statistical tools such as receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) need to be expanded to address three-category classification problem. Previous authors have suggest various ways to model the extension of AUC but not the ROC surface. Only simple parametric approaches are proposed for modeling the ROC measure under the assumption that test results all follow normal distributions. We study the estimation methods of three-dimensional ROC surfaces with nonparametric and semiparametric estimators. Asymptotical results are provided as a basis for statistical inference. Simulation studies are performed to assess the validity of our proposed methods in finite samples. We consider an Alzheimer's disease example from a clinical study in the US as an illustration. The nonparametric and semiparametric modelling approaches for the three way ROC analysis can be readily generalized to diagnostic problems with more than three classes.     

On pseudo-values for regression analysis in competing risks models

For regression on state and transition probabilities in multi-state models Andersen et al. (Biometrika 90:15–27, 2003) propose a technique based on jackknife pseudo-values. In this article we analyze the pseudo-values suggested for competing risks models and prove some conjectures regarding their asymptotics (Klein and Andersen, Biometrics 61:223–229, 2005). The key is a second order von Mises expansion of the Aalen-Johansen estimator which yields an appropriate representation of the pseudo-values. The method is illustrated with data from a clinical study on total joint replacement. In the application we consider for comparison the estimates obtained with the Fine and Gray approach (J Am Stat Assoc 94:496–509, 1999) and also time-dependent solutions of pseudo-value regression equations.     

人口普查覆盖误差估计方法综述

人口普查工作的质量主要体现在覆盖误差的规模上.人口统计学家创建了估计人口普查覆盖误差的方法.有些方法利用独立于人口普查本身的信息,另外一些方法则利用人口行政记录的信息.由于每种方法都有其特定的形成背景和适用范围,因而没有适合于所有国家和地区的通用方法.通过对美国、新西兰、澳大利亚、英国和中国的人口普查覆盖误差估计方法进行了较为详细的介绍,说明了这些方法的使用情况.研究表明,任何一种估计方法都有其局限性,需要不断改进与完善.     

健康在多大程度上引致贫困脆弱性——基于CHNS农村数据的经验分析

贫困脆弱性的产生,很大程度上归因于居民健康水平的下降.在阐述健康引致贫困理论机制的基础上,基于CHNS在2000-2009年间追踪调查数据,对贫困脆弱性和健康效用指数HUI进行测度,估计并分析健康对贫困脆弱性的影响与内在机制.研究发现:居民健康水平的恶化会使其面临更高的贫困脆弱性,居民健康水平每下降10％,贫困脆弱性大约会上升6％;健康影响贫困脆弱性的作用机制中,物质资本和社会资本渠道被证明是相对有效的,而人力资本渠道尽管体现出微弱效应,但尚未在统计上得到显著性验证.因此,制订前瞻性的反贫政策应着眼于建立健康风险防范机制,包括提高农村医疗保障水平和重大疾病救助力度,并增加农村公共服务的投入,以促进其均衡化发展.     

Bayesian influence diagnostics in radiocarbon dating

Linear models constitute the primary statistical technique for any experimental science. A major topic in this area is the detection of influential subsets of data, that is, of observations that are influential in terms of their effect on the estimation of parameters in linear regression or of the total population parameters. Numerous studies exist on radiocarbon dating which propose a value consensus and remove possible outliers after the corresponding testing. An influence analysis for the value consensus from a Bayesian perspective is developed in this article.     

A joint modelling approach for clustered recurrent events and death events

In dental implant research studies, events such as implant complications including pain or infection may be observed recurrently before failure events, i.e. the death of implants. It is natural to assume that recurrent events and failure events are correlated to each other, since they happen on the same implant (subject) and complication times have strong effects on the implant survival time. On the other hand, each patient may have more than one implant. Therefore these recurrent events or failure events are clustered since implant complication times or failure times within the same patient (cluster) are likely to be correlated. The overall implant survival times and recurrent complication times are both interesting to us. In this paper, a joint modelling approach is proposed for modelling complication events and dental implant survival times simultaneously. The proposed method uses a frailty process to model the correlation within cluster and the correlation within subjects. We use Bayesian methods to obtain estimates of the parameters. Performance of the joint models are shown via simulation studies and data analysis.