Logistic regression analyses for indirect data

The article’s topic is logistic regression for direct data on the covariates, but indirect data on the endogenous variable. The indirect data may result from a privacy-protecting survey procedure for sensitive characteristics or from statistical disclosure control. Various procedures to generate the indirect data exist. However, we show that it is possible to develop a general approach for logistic regression analyses with indirect data that covers many procedures. We first derive a general algorithm for the maximum likelihood estimation and a general procedure for variance estimation. Subsequently, lots of examples demonstrate the broad applicability of our general framework.     

Hybrid pairwise‐likelihood estimation methods for incomplete longitudinal binary data

In longitudinal data, missing observations occur commonly with incomplete responses and covariates. Missing data can have a ‘missing not at random’ mechanism, a non‐monotone missing pattern, and moreover response and covariates can be missing not simultaneously. To avoid complexities in both modelling and computation, a two‐stage estimation method and a pairwise‐likelihood method are proposed. The two‐stage estimation method enjoys simplicities in computation, but incurs more severe efficiency loss. On the other hand, the pairwise approach leads to estimators with better efficiency, but can be cumbersome in computation. In this paper, we develop a compromise method using a hybrid pairwise‐likelihood framework. Our proposed approach has better efficiency than the two‐stage method, but its computational cost is still reasonable compared to the pairwise approach. The performance of the methods is evaluated empirically by means of simulation studies. Our methods are used to analyse longitudinal data obtained from the National Population Health Study.     

Analysis of dose-response in flexible dose titration clinical studies

Assessing dose-response from flexible-dose clinical trials (e.g., titration or dose escalation studies) is challenging and often problematic due to the selection bias caused by 'titration-to-response'. We investigate the performance of a dynamic linear mixed-effects (DLME) model and marginal structural model (MSM) in evaluating dose-response from flexible-dose titration clinical trials via simulations. The simulation results demonstrated that DLME models with previous exposure as a time-varying covariate may provide an unbiased and efficient estimator to recover exposure-response relationship from flexible-dose clinical trials. Although the MSM models with independent and exchangeable working correlations appeared to be able to recover the right direction of the dose-response relationship, it tended to over-correct selection bias and overestimated the underlying true dose-response. The MSM estimators were also associated with large variability in the parameter estimates. Therefore, DLME may be an appropriate modeling option in identifying dose-response when data from fixed-dose studies are absent or a fixed-dose design is unethical to be implemented.     

Expected loss functions as additional measures to assess performance of multiple testing procedures for combination drug dose finding

There are several measures that are commonly used to assess performance of a multiple testing procedure (MTP). These measures include power, overall error rate (family‐wise error rate), and lack of power. In settings where the MTP is used to estimate a parameter, for example, the minimum effective dose, bias is of interest. In some studies, the parameter has a set‐like structure, and thus, bias is not well defined. Nevertheless, the accuracy of estimation is one of the essential features of an MTP in such a context. In this paper, we propose several measures based on the expected values of loss functions that resemble bias. These measures are constructed to be useful in combination drug dose response studies when the target is to identify all minimum efficacious drug combinations. One of the proposed measures allows for assigning different penalties for incorrectly overestimating and underestimating a true minimum efficacious combination. Several simple examples are considered to illustrate the proposed loss functions. Then, the expected values of these loss functions are used in a simulation study to identify the best procedure among several methods used to select the minimum efficacious combinations, where the measures take into account the investigator's preferences about possibly overestimating and/or underestimating a true minimum efficacious combination. The ideas presented in this paper can be generalized to construct measures that resemble bias in other settings. These measures can serve as an essential tool to assess performance of several methods for identifying set‐like parameters in terms of accuracy of estimation. Copyright © 2012 John Wiley & Sons, Ltd.     

基于瓶颈负荷的BTO供应链响应时间优化

供应商生产的低效率是BTO供应链实际运作过程中的瓶颈,主要表现为供应链整体响应时间长和在制品库存高.针对该类供应链的瓶颈特点,利用排队模型建立了一种基于瓶颈负荷的BTO供应链响应时间优化策略.然后,通过算例分析了订单数量、等待订单数量和产能利用率,以及系统内的概率分布等参数对在制品库存水平和供应链整体响应时间的影响.最后,得出的结论表明,基于瓶颈负荷的控制对缩短供应链整体响应时间和在制品库存水平的控制均是有效的.     

An Integrated Methodology for Assessment and Selection of the Project Risk Response Actions

In a systematic process of project risk management, after risk assessment is implemented, the risk analysts encounter the phase of assessment and selection of the project risk response actions (RA). As indicated by many researchers, there are less systematic and well-developed solutions in the area of risk response assessment and selection. The present article introduces a methodology including a modeling approach with the objective of selecting a set of RA that minimizes the undesirable deviation from achieving the project scope. The developed objective function comprises the three key success criteria of a project, namely, time, quality, and cost. Our model integrates overall project management into the project risk response planning (P2RP). Furthermore, the proposed model stresses on an equivalent importance for both "risk" and "response." We believe that applying the proposed model helps the project risk analyst in most effective and efficient manner dealing with his or her complicated RA selection problems. The application of the proposed model was implemented in projects in the construction industry in which it showed tremendous time, cost, and quality improvements.     

Improved CUSUM charts for monitoring process mean

In this paper, we propose new cumulative sum (CUSUM) and Shewhart-CUSUM (SCUSUM) control charts for monitoring the process mean using ranked-set sampling (RSS) and ordered RSS (ORSS) schemes. The proposed CUSUM charts include the Crosier's CUSUM (CCUSUM) and Shewhart-CCUSUM (SCCUSUM) charts using RSS, and the CUSUM, CCUSUM, SCUSUM and SCCUSUM charts using ORSS. Moreover, fast initial response features are also attached with these CUSUM charts to improve their sensitivities for an initial out-of-control situation. Monte Carlo simulations are used to compute the run length characteristics of the proposed CUSUM charts. Upon comparing the run length performances of the CUSUM charts, it turns out that the proposed CUSUM charts are more sensitive than their existing counterparts. A real dataset is used to explain the implementation of the proposed CUSUM charts.     

“是其所不是”：萨特戏剧的肯定性命题

萨特存在主义人生价值论包含的＂是其所不是的＂肯定性命题,在萨特戏剧里主要表现为自由与自由选择问题。自由与自由选择问题告诉人们,客观的规律可以规定人的现实处境,但不能限定人对待现实处境的主观态度,自由与自由选择还必须承担伦理责任,从而为价值论的主观追求充实了社会现实意义。     

近代东北灾荒史论略

本文为讨论1840年-1949年间中国东北地区灾荒以及民众应对灾荒的历史沿革的专题论文,即从近代东北灾荒的历时性分布、灾荒成因、灾荒影响、从无效应对到有效应对、灾荒救助与社会进步等几个方面进行讨论,概述灾荒对近代东北社会的影响,论述卫生防疫、慈善救助等救灾措施,并从社会生活史的角度解析近代东北社会近代化的历程及与民众的互动关系。     

中国建立稻谷期货市场话语权研究——基于中、美、泰三国市场的实证分析

作为全球最大的粮食生产国和消费国,早籼稻期货的推出引发了社会对我国能否成为世界粮食定价中心、能否拥有世界粮价话语权的关注。基于向量自回归（VAR）模型、方差分解、脉冲响应函数等计量方法,对我国郑州期货市场（CZCE）、美国芝加哥商品交易所（CBOT）及泰国农产品期货交易所（AFET）3个最主要的稻谷期货市场之间的联动性及影响机制进行了研究,得出三者之间确实存在协整关系,且郑州期货价格引导芝加哥期货价格。此外,世界稻谷期货市场总方差中来自于CZCE的方差为39.43%,来自于CBOT的方差为26.58%,来自于AFET的方差为33.99%。鉴于现有的市场影响力和地位,我国要努力通过完善国内市场和健全期货市场等方式获得国际稻谷市场的定价权和话语权。