Models for the analysis of C-reactive protein in statin trials

Elevation in C-reactive protein (CRP) is an independent risk factor for cardiovascular disease progression and levels are reduced by treatment with statins. However, on-treatment CRP, given baseline CRP and treatment, is not normally distributed and outliers exist even when transformations are applied. Although classical non-parametric tests address some of these issues, they do not enable straightforward inclusion of covariate information. The aims of this study were to produce a model that improved efficiency and accuracy of analysis of CRP data. Estimation of treatment effects and identification of outliers were addressed using controlled trials of rosuvastatin. The robust statistical technique of MM-estimation was used to fit models to data in the presence of outliers and was compared with least-squares estimation. To develop the model, appropriate transformations of the response and baseline variables were selected. The model was used to investigate how on-treatment CRP related to baseline CRP and estimated treatment effects with rosuvastatin. On comparing least-squares and MM-estimation, MM-estimation was superior to least-squares estimation in that parameter estimates were more efficient and outliers were clearly identified. Relative reductions in CRP were higher at higher baseline CRP levels. There was also evidence of a dose-response relationship between CRP reductions from baseline and rosuvastatin. Several large outliers were identified, although there did not appear to be any relationships between the incidence of outliers and treatments. In conclusion, using robust estimation to model CRP data is superior to least-squares estimation and non-parametric tests in terms of efficiency, outlier identification and the ability to include covariate information.     

Exponentially weighted moving average charts for correlated multivariate Poisson processes

In this article, we study exponentially weighted moving average (EWMA) control schemes to monitor the multivariate Poisson distribution with a general covariance structure, so that the practitioner can simultaneously monitor multiple correlated attribute processes more effectively. The statistical performance of the charts is assessed in terms of the run length properties and compared against other mainstream attribute control schemes. The application of the proposed methods to real-life and simulated datasets is demonstrated.     

Rank and response: A field experiment on peer information and water use behavior

Perception of peer rank, or how we perform relative to our peers, can be a powerful motivator. While research exists on the effect of social information on decision making, there is less work on how ranked comparisons with our peers influence our behavior. This paper outlines a field experiment conducted with 3896 households in Castro Valley, California, which uses household mailers with various forms of social information and peer rank messaging to motivate water conservation. The experiment tests the effect of a visible peer rank on water use, and how the competitive framing of rank information influences behavioral response. The results show that households with relatively low or high water use in the pre-treatment period responded differently to how rank information was framed. I find that a neutrally-framed peer rank caused a small “boomerang effect” (i.e., an increase in average water use) for low water use households, but this effect was eliminated by competitive framing. At the same time, a competitively-framed peer rank demotivated high water use households, increasing their average water use over the full period of the experiment. This result is supported by evidence that the competitive frame on rank information increased water use for households who ranked “last” in the peer group – a detrimental “last place effect” from competitively-framed rankings.     

Exploitation aversion: When financial incentives fail to motivate agents

Studies of the principal-agent relationship find that monetary incentives work in many instances but that they can also backfire. Various mechanisms for this failure have been examined (e.g., intrinsic motivation, image concerns). We posit that an aversion to being exploited, i.e., being used instrumentally for another’s benefit, can also cause incentives to fail. Using an experiment we find that compliance is lower for exploitative principals compared to neutral ones despite using the same contracts. To corroborate our results we show that surveyed “exploitation aversion” mediates this effect. Our results have implications for the design and implementation of incentives within organizations.     

Rent-seeking and competitive preferences

In this experiment, I examine the extent to which competitive social preferences can explain over-bidding in rent-seeking contests. The Human treatment is a standard two-player contest. In the Robot treatment, a single player bids against a computerized player, eliminating potential social preference motives. The results show no difference in bids between treatments at the aggregate level. Further analysis shows evidence of heterogeneous treatment effects between impulsive and reflective subjects. Moreover, impulsive subjects are more likely than reflective subjects to deviate qualitatively from the shape of the theoretical best response function.     

关于Feigenbaum型泛函方程的C^1解

利用Schauder不动点定理、自同胚和紧凸子集的相关性质研究Feigenbaum型泛函方程的连续可微解的存在性和唯一性.     

基于Delphi/Access的C/S系统设计

C/S系统采用Access作后台数据库,具有性能稳定、数据交换迅速、数据安全、维护方便等特点,可视化编程语言Delphi具有丰富的编程环境、友好的界面、高速的编译器、强大的数据库开发功能,文章介绍了基于Delphi/Access的C/S系统软、硬件设计方法和技术。     

基于C／S和B／S混合模式的多媒体电子阅览室管理系统设计

高职院校多媒体电子阅览室是用户获取信息和学习的重要场所,如何能进一步完善和发展它需要有效的管理系统和具有更高素质的管理队伍。从网络化、一体化、多元化的理念出发,采用三层C/S和B/S两种混合模式,在用户管理,资源管理,安全管理三个方面展开论述,为现代多媒体电子阅览室提出了方便实用、安全有效的管理系统设计方案,以供大家探讨。     

B2C电子商务顾客满意度测评研究

文章在参考已有研究成果的基础上,构建了B2C电子商务顾客满意度测评模型及其评价指标体系,并运用模糊综合评判法对某电子商务公司进行实证测评,最后对测评结果进行分析,并提出相应的对策以提升顾客满意度.