用数据挖掘技术实现多因素实验设计

目的本文介绍如何用数据挖掘技术实现同水平和混合水平多因素实验设计的方法，即独立设计；总结和讨论了独立设计的特点。方法以同水平或混合水平多因素析因设计矩阵为母体，不增加任何限定条件，仅考察各实验点对其余实验点的影响，采用“主成分分析、聚类分析和规则归纳”等数据挖掘技术相结合的方法，先将全部实验点快速分类，然后，再进行聚类，可将此矩阵分解成一系列彼此互不重叠的独立设计矩阵。结果不仅发现用数据挖掘技术实现多因素实验设计是可行的，而且，发现了除正交设计、均匀设计以外的一些可用于多因素实验设计的特殊设计。结论独立设计是一类涵盖面很宽的多因素实验设计方法，它不仅集“析因设计、分式析因设计、正交设计、均匀设计”于一身，还包含有突出“中间水平”或“极端水平”的特殊设计。与正交设计和均匀设计相比较，独立设计的适用面更宽、灵活性更大，具有极大的理论研究价值和广阔的实际应用前景。     

浅谈医疗综合楼设计中的节能措施

在医院建设中，医疗综合楼建设量越来越多，其特点是人员流动性强、功能分区多，能耗高。因此从建设前期规划和方案设计时就应该注重节能设计，其后各个设备专业都从节能方面出发，进行施工图设计，以达到较好的节能效果。本文分析了医疗综合楼的特点和能耗特点，从建筑设计、空调通风、电气、水等各系统中分析系统节能设计的措施，并对节能效果进行了分析。     

SPSS13.0在空白列正交试验设计及其数据处理中的应用

正交试验设计（orthogonal experiment design）对多因素、多水平的试验具有设计、计算简便、节省实验单元、统计效率高等优点，故在药物拆方、药品制备工艺、试验条件的优化等方面运用广泛。但是利用SPSS系统随机产生的正交设计表，进行正交试验设计及其数据处理方面，仅有无空列非重复正交试验设计的个案报道；在无空列重复正交试验设计（也称有重复正交试验设计）和空白列正交试验设计方面，未见报道。本文利用SPSS系统随机产生的无空列重复正交试验设计表及空白列正交试验设计表，     

同水平析因设计矩阵的分解结果及其特点

目的介绍同水平析因设计矩阵的分解方法、分解结果及其特点,为多因素试验设计提供一种有效方法.方法以n水平(n≥3)的同水平多因素析因设计矩阵为基本的设计矩阵,不增加任何限定条件,仅考察各试验点对其余试验点的影响,采用"主成分分析、聚类分析和规则归纳"等数据挖掘技术相结合的方法,可将此矩阵分解成一系列彼此互不重叠的独立设计矩阵.结果独立设计矩阵具有一些很好的特点,有些本身就是正交设计,有些本身就是均匀设计,还有些是它们所不包含的特殊设计,这些设计一般都是比较理想的多因素试验设计.结论独立设计不仅涵盖了多因素析因设计、分式析因设计、正交设计、均匀设计,还有一些是具有实用性的特殊设计,它是一类具有很高理论研究价值和实际应用前景的综合性极强的多因素试验设计方法.     

四会市疾病预防控制中心新实验室设计简介

目的：自非典之后，国家加大了公共卫生建设的投入。如何有效利用政府投入资金设计建设一个既经济实用，又不失具有先进性的公共卫生实验室，是目前县级疾控机构实验室建设的重要课题。方法：首先应多参观多学习，借鉴别人先进经验；查阅有关规范，结合各自实验室工作实际，规划初步草图，然后交由装修设计专业公司进行图纸专业化，再由实验室专业装修公司进行装修。结果：四会市疾控中心新实验室无论布局以及安全性、实用性都基本合理。结论：参观学习，是借鉴别人先进经验，不是互相攀比，也不是照搬照抄，而是结合四会的实际，参考有关规范，建设具有四会特色的县级疾控中心实验室。     

要在研究设计上下功夫

要在研究设计上下功夫上海医科大学２０００３２詹绍康不论是科学研究工作者和研究论文的作者，还是研究论文的读者和科技成果的应用者，部应该在研究设计方面多下些功夫。研究者要务求设计正确合理，读者要通过对研究设计的推敲，来对研究结果的价值作出判断。一、在接受...     

PDC-1膀胱功能电刺激器的原理及其动物试验

脊髓损伤(Spinal Cord Injury，SCI)导致截瘫的病人多数伴有膀胱功能障碍，患者表现为膀胱内压很高，残余尿量多，常常引起尿路感染和肾积水，而肾功能衰竭是此类患者晚期死亡的主要原因。为解决此类病人的排尿功能障碍，根据不同类型肌肉在电刺激下反应不同的机理自行研制开发了一种新型膀胱功能电刺激器，本文对该电刺激器的设计原理进行了详细的分析。该电刺激器设计分为信号产生、发射和接收三部分，带有单片机控制，通过液晶显示片医生可以根据病人的情况方便地设置信号幅值、脉宽、频率、占空比等参数，以便达到最佳的排尿效果。通过4条犬5次动物试验，取得了良好的效果。     

社会活动：爱心义卖

设计意图：琪琪小朋友的爸爸、妈妈都患有很严重的疾病，她只能与多病的奶奶相依为命。班上的孩子们得知这些情况后，都主动地给她以关心和帮助，稚嫩的行动中自然流露出孩子们的纯真爱心。于是，我设计了这节活动，利用发生在孩子们身边真实的人和事对他们进行爱的教育，让他们在实实在在地感受爱的含义，深刻体验帮助别人所带来的快乐。     

本刊对统计学方法的要求

研究设计：应告知研究设计的名称和主要方法。如调查设计（分为前瞻性、回顾性还是横断面调查研究），实验设计（应告知具体的设计类型，如自身配对设计、成组设计、交叉设计、析因设计、正交设计等），临床试验设计（应告知属于第几期临床试验，采用了何种盲法措施等）；     

应用Excel 2000进行随机设计

随机设计是实验研究设计的基本原则之一.微软公司的电子表格软件Excel 2000提供了约350多个函数,利用其中的随机数函数RAND及其他功能可很好地进行实验的随机设计,方法方便、简捷、灵活.     

On statistical analysis for placebo-challenging designs in clinical trials

In clinical trials, appropriate designs are often chosen to address scientific/medical questions of particular interest to the investigator. For a chosen statistical design, however, standard statistical procedures may not be applicable owing to the nature of the design. In this paper we examine statistical methods for analysis of data collected from a placebo-challenging design which is often considered for assessment of the efficacy of drug products for indication of erectile dysfunction. An example concerning a clinical trial conducted with 120 male patients with erectile dysfunction is used to illustrate the derived statistical methods. Some recommendations to the randomization procedure for the study design of this kind are also made.     

An overview of variance inflation factors for sample-size calculation

For power and sample-size calculations, most practicing researchers rely on power and sample-size software programs to design their studies. There are many factors that affect the statistical power that, in many situations, go beyond the coverage of commercial software programs. Factors commonly known as design effects influence statistical power by inflating the variance of the test statistics. The authors quantify how these factors affect the variances so that researchers can adjust the statistical power or sample size accordingly. The authors review design effects for factorial design, crossover design, cluster randomization, unequal sample-size design, multiarm design, logistic regression, Cox regression, and the linear mixed model, as well as missing data in various designs. To design a study, researchers can apply these design effects, also known as variance inflation factors to adjust the power or sample size calculated from a two-group parallel design using standard formulas and software.     

医学研究中的统计图形规范

统计图形历史悠久,是呈现医学研究设计、结果、结论的重要方式。纵观近年来中英文学术期刊中的统计图形可知,当前医学研究人员对统计图形的科学性和规范性的把握尚有不足。本文以NEJM、Lancet、JAMA、The BMJ四大权威医学期刊中统计图形的要求为切入点,总结出统计图形的技术要求、设计要点以及常见统计图形的实用条件、注意事项,以供医学研究者参考。     

A simulation study of three sequential methods for the comparison of two treatment groups when the response criterion is censored

Three recent sequential methods, group sequential analysis (GSA), the sequential probability ratio test (SPRT) and the triangular test (TT) are well suited to randomized clinical trials with a censored response criterion, as they do not require matched pairs of patients. We undertook a simulation study to investigate their statistical properties and to compare these three methods with the fixed-sample design. Our results suggest that the three methods have the expected statistical properties for size and power; they allow an important reduction of the average number of events before stopping, except with GSA when there is no treatment difference; the triangular test (closed design) appears the optimal design, as the variance of the number of events is smaller than with the sequential probability ratio test (open design) and analysis after every twenty new events does not alter the statistical properties of these sequential methods and enhances their usefulness.     

Designing linked micromap plots for states with many counties

This paper describes the design of linked micromap plots for showing county estimates on a state by state basis. The linked micromap template was specifically developed to represent spatially indexed statistical summaries. Each plot shows regional names, spatial patterns and statistical patterns while linking them all together. Thus the design is useful for communicating summaries from a host of health and environmental studies. The specific design challenge in this paper is to create one-page plots for the states with 60 to 120 counties. While the county names and micromaps take up substantial space, the three examples demonstrate that there is sufficient space to represent two variables. The basic design has the potential for showing more. Consequently the new designs are suitable for presenting sophisticated summaries.     

Longitudinal Assessment Design and Statistical Power for Detecting an Intervention Impact

In evaluating randomized control trials (RCTs), statistical power analyses are necessary to choose a sample size which strikes the balance between an insufficient and an excessive design, with the latter leading to misspent resources. With the growing popularity of using longitudinal data to evaluate RCTs, statistical power calculations have become more complex. Specifically, with repeated measures, the number and frequency of measurements per person additionally influence statistical power by determining the precision with which intra-individual change can be measured as well as the reliability with which inter-individual differences in change can be assessed. The application of growth mixture models has shown that the impact of universal interventions is often concentrated among a small group of individuals at the highest level of risk. General sample size calculations were consequently not sufficient to determine whether statistical power is adequate to detect the desired effect. Currently, little guidance exists to recommend a sufficient assessment design to evaluating intervention impact. To this end, Monte Carlo simulations are conducted to assess the statistical power and precision when manipulating study duration and assessment frequency. Estimates were extracted from a published evaluation of the proximal of the Good Behavior Game (GBG) on the developmental course of aggressive behavior. Results indicated that the number of time points and the frequency of assessments influence statistical power and precision. Recommendations for the assessment design of longitudinal studies are discussed.     

Effect of sample design in the analysis of complex surveys. Application to the health survey of Catalonia

OBJECTIVE: To illustrate the way in which a sample design can be easily incorporated into the statistical analysis of complex surveys to obtain correct estimates. METHODS: A statistical program (STATA) was used to analyze the Catalan Health Survey (Spain) for the year 1994. RESULTS: If the sample design is taken into account, the estimates are unbiased. If only the weights are taken into account, unbiased point estimates are obtained, but the standard errors tend to be underestimated. CONCLUSIONS: The current availability of statistical programs that allow to incorporate easily the sample design should encourage researchers to better analyze their surveys.     

Inappropriate Survey Design Analysis of the Korean National Health and Nutrition Examination Survey May Produce Biased Results

Objectives

The inherent nature of the Korean National Health and Nutrition Examination Survey (KNHANES) design requires special analysis by incorporating sample weights, stratification, and clustering not used in ordinary statistical procedures.

Methods

This study investigated the proportion of research papers that have used an appropriate statistical methodology out of the research papers analyzing the KNHANES cited in the PubMed online system from 2007 to 2012. We also compared differences in mean and regression estimates between the ordinary statistical data analyses without sampling weight and design-based data analyses using the KNHANES 2008 to 2010.

Results

Of the 247 research articles cited in PubMed, only 19.8% of all articles used survey design analysis, compared with 80.2% of articles that used ordinary statistical analysis, treating KNHANES data as if it were collected using a simple random sampling method. Means and standard errors differed between the ordinary statistical data analyses and design-based analyses, and the standard errors in the design-based analyses tended to be larger than those in the ordinary statistical data analyses.

Conclusions

Ignoring complex survey design can result in biased estimates and overstated significance levels. Sample weights, stratification, and clustering of the design must be incorporated into analyses to ensure the development of appropriate estimates and standard errors of these estimates.     

基于医疗工程辅助设计平台的综合医院前期策划探究

通过对既有综合医院建筑数据进行统计、整理、分析,借助计算机软件技术、云端服务、统计学理论等手段,形成基于数据可视化、多方协同的医疗工程辅助设计数据平台,以弥补综合医院前期策划的不足。从项目管理、规范查询、辅助设计三大功能模块出发,为医院建筑设计相关从业人员提供直观的数字及图形参考,提高多方沟通和工作效率。     

医学研究中统计图形的构成要素和设计要点

统计图形作为医学研究结果可视化的重要方法,可清晰地展示研究结果和重点。然而,如何设计一幅好的统计图形,目前国内外尚无权威且统一的原则,且对于统计图形设计原则缺乏认识,可能会掩盖成果亮点甚至曲解研究结果。鉴于此,本文结合实例,阐述统计图形的构成要素和设计原则,供国内医学研究者参考。