Strategic Choice of Variability in Multiround Contests and Contests with Handicaps

Variability can be an important strategic variable in a contest. We study optimal strategies involving choice of variability in contests with fixed and probabilistic targets, one-round and multiround contests, contests with and without handicaps, and situations where one contestant can modify variability as well as those in which all contestants have this opportunity. A contestant should maximize variability in a weak position (low mean, high handicap, or low previous performance) and minimize variability in a strong position. In some cases, only these extremes should be used. In other cases, intermediate levels of variability are optimal when the contestant's position is neither too weak nor too strong.     

论应对入世的五大关系——兼析认识WTO的若干误区

本文着眼于中国入世后经济生活面临的新形势、新环境、新任务和新要求,比较系统地分析了应对入世工作中面对与应对、权利与义务、改革与开放、开放与安全、内需与外需五大关系。辩证地分析各对关系中博弈与共赢的内在联系、实质内涵、现实影响及认识上的误区。     

构建高校教师党员联系班级长效机制的思考

本文分析高校教师党员联系班级的重要意义,提出其工作重点,并就如何构建长效机制进行探究。     

Variability and Uncertainty in Swedish Exposure Factors for Use in Quantitative Exposure Assessments

Information of exposure factors used in quantitative risk assessments has previously been compiled and reported for U.S. and European populations. However, due to the advancement of science and knowledge, these reports are in continuous need of updating with new data. Equally important is the change over time of many exposure factors related to both physiological characteristics and human behavior. Body weight, skin surface, time use, and dietary habits are some of the most obvious examples covered here. A wealth of data is available from literature not primarily gathered for the purpose of risk assessment. Here we review a number of key exposure factors and compare these factors between northern Europe—here represented by Sweden—and the United States. Many previous compilations of exposure factor data focus on interindividual variability and variability between sexes and age groups, while uncertainty is mainly dealt with in a qualitative way. In this article variability is assessed along with uncertainty. As estimates of central tendency and interindividual variability, mean, standard deviation, skewness, kurtosis, and multiple percentiles were calculated, while uncertainty was characterized using 95% confidence intervals for these parameters. The presented statistics are appropriate for use in deterministic analyses using point estimates for each input parameter as well as in probabilistic assessments.     

近代四川城市水源结构的空间差异性研究

基于清末民国旧方志、新中国建国后编修的新方志、东亚同文书院的饮水调查以及民国档案中的饮水统计，对近代四川123个城市的水源结构作了复原。以“四川”或“地貌区”为空间级考量，近代四川城市水源结构皆存在明显的空间差异。以井水为主的城市集中在川西平原与川中丘陵北部，以河水为主的城市集中在川东平行岭谷与盆周边缘山地，以溪泉为主的城市散布在盆周边缘山地、川西南山地与川西北高原。地理环境与取用便捷性是影响近代四川城市水源结构的主要因素，涵括“地下水位高低与凿井难易度”“城市是否濒临江河”“城市濒临江河干流或支流的差异”三个方面的影响因子。     

Response model analysis for robust design experiments

Taguchi's robust design technique, also known as parameter design, focuses on making product and process designs insensitive (i.e., robust) to hard to control variations. In some applications, however, his approach of modeling expected loss and the resulting “product array” experimental format leads to unnecessarily expensive and less informative experiments. The response model approach to robust design proposed by Welch, Ku, Yang, and Sacks (1990), Box and Jones (1990), Lucas (1989), and Shoemaker, Tsui and Wu (1991) offers more flexibility and economy in experiment planning and more informative modeling. This paper develops a formal basis for the graphical data-analytic approach presented in Shoemaker et al. In particular, we decompose overall response variation into components representing the variability contributed by each noise factor, and show when this decomposition allows us to use individual control-by-noise interaction plots to minimize response variation. We then generalize the control-by-noise interaction plots to extend their usefulness, and develop a formal analysis strategy using these plots to minimize response variation.     

Interlitter Response Variability in a Threshold Dose-Response Model

In this article, we extend a previously formulated threshold dose-response model with random litter effects that was applied to a data set from a developmental toxicity study. The dose-response pattern of the data indicates that a threshold dose level may exist. Additionally, there is noticeable variation between the responses across the dose levels. With threshold estimation being critical, the assumed variability structure should adequately model the variation while not taking away from the estimation of the threshold as well as the other parameters directly involved in the dose-response relationship. In the prior formulation, the random effect was modeled assuming identical variation in the interlitter response probabilities across all dose levels, that is, the model had a single parameter to account for the interlitter variability. In this new model, the random effect is modeled as having different response variability across dose levels, that is, multiple interlitter variability parameters. We performed the likelihood ratio test (LRT) to compare our extended model to the previous model. We conducted a simulation study to compare the bias of each model when fit to data generated with the underlying parametric structure of the opposing model. The extended threshold dose-response model with multiple response variation was less biased.