长效钙离子拮抗剂对动态血压季节性变异的研究

目的探讨苯磺酸氨氯地平片对动态血压季节性变异的影响。方法 96名轻中度原发性高血压患者随机分为3组,即非洛地平缓释片组（F组）、硝苯地平控释片（X组）和苯磺酸氨氯地平片（A组）,每组32例患者,所有患者用安慰剂洗脱2周后分别给予非洛地平缓释片5mg/d、硝苯地平控释片30mg/d和苯磺酸氨氯地平片5mg/d治疗,1月后血压未达标加用贝那普利片10mg/d。所有患者均于冬季和夏季分别行24小时动态血压监测,观察血压晨峰（MBPS）和冬夏两季血压达标率变化。结果无论24小时、日间还是夜间,冬季A组血压达标率（78.1%,78.1%,75.0%）均明显高于F组（62.5%,65.6%,56.3%）和X组（65.6%,68.8%,65.6%）（均P〈0.01）。冬季A组MBPS（33.7±9.7mmHg）显著低于F组（38.0±11.4mmHg,P〈0.01）和X组（36.9±10.9mmHg,P〈0.05）。结论与非洛地平缓释片和硝苯地平控释片比较,苯磺酸氨氯地平片降低血压季节性变异更明显,冬季24小时动态血压达标率更高。     

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.     

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.     

Analysis of local influence in geostatistics using Student's t-distribution

This article aims to estimate parameters of spatial variability with Student's t-distribution by the EM algorithm and present the study of local influence by means of two methods known as likelihood displacement and Q-displacement of likelihood, both using Student's t-distribution with fixed degrees of freedom (ν). The results showed that both methods are effective in the identification of influential points.     

Measuring Gross Flows in the Labor Force: An Overview of a Special Conference

The measurement of flows in the American labor market has challenged researchers for years. Several problems, including response variability, rotation group bias, and matching errors, hinder accurate measurement of the flows. The Bureau of the Census and the Bureau of Labor Statistics jointly sponsored a conference to examine these problems, present current research on solutions to the problems, and submit recommendations for improving the data. Recommendations include procedural changes in the Current Population Survey as well as new estimation techniques.     

Integrating Uncertainty and Interindividual Variability in Environmental Risk Assessment

An integrated, quantitative approach to incorporating both uncertainty and interindividual variability into risk prediction models is described. Individual risk R is treated as a variable distributed in both an uncertainty dimension and a variability dimension, whereas population risk I (the number of additional cases caused by R) is purely uncertain. I is shown to follow a compound Poisson-binomial distribution, which in low-level risk contexts can often be approximated well by a corresponding compound Poisson distribution. The proposed analytic framework is illustrated with an application to cancer risk assessment for a California population exposed to 1,2-dibromo-3-chloropropane from ground water.