A nonparametric statistical approach in noisy chaos identification

Data resulting from some deterministic dynamic systems may appear to be random. To distinguish these kinds of data from random data is a new challenge for statisticians. This paper develops a nonparametric statistical test procedure for distinguishing noisy chaos from i. i. d. random processes. The procedure can be easily implemented by computer and is very effective in identifying low dimensional chaos in certain instances.     

Data quality: A statistical perspective

We present the old-but-new problem of data quality from a statistical perspective, in part with the goal of attracting more statisticians, especially academics, to become engaged in research on a rich set of exciting challenges. The data quality landscape is described, and its research foundations in computer science, total quality management and statistics are reviewed. Two case studies based on an EDA approach to data quality are used to motivate a set of research challenges for statistics that span theory, methodology and software tools.     

Robust regression:a weighted least squares approach

Robust regression has not had a great impact on statistical practice, although all statisticians are convinced of its importance. The procedures for robust regression currently available are complex, and computer intensive. With a modification of the Gaussian paradigm, taking into consideration outliers and leverage points, we propose an iteratively weighted least squares method which gives robust fits. The procedure is illustrated by applying it on data sets which have been previously used to illustrate robust regression methods.It is hoped that this simple, effective and accessible method will find its use in statistical practice.     

Omnitab-a simple language for statistical computations

The OMNITAB system of computer programming provides a simple, yet extremely versatile means of communicating with the computer using simple English words and phrases, It is written in FORTRAN and is available for implementation on UNIVAC 1108, IBM 360, Burroughs 5500 and CDC 6600 equipment. It is based on a worksheet, stored in the computer, which is a two dimensional array easy to visualize even by beginners. The system has particular use for students of statistics, of all ages, in that it allows them to interact with the data without requiring that they master any diffiicult and esoteric (for statisticians) computer skills. The programming system is described together with several applications to statistical problems. Full program documentation is available from the authors.     

Statisticians in European regulatory agencies

The UK body of statisticians in the pharmaceutical industry, PSI, has called on heads of European regulatory agencies responsible for assessing applications for marketing authorizations for new medicines in the EU to employ full time statisticians. In order to assess the present situation a survey has been conducted to identify the number of agencies employing one or more full time statisticians. Out of 29 responding agencies, 12 employed one or more statisticians on a full time basis, whereas 17 did not. Among these 17, 7 involved external experts on a regular basis, 5 involved external statisticians on a case‐by‐case basis, whereas 5 never involved external statistical expertise. Failure to involve statisticians in the assessment of efficacy and safety of medicines does not automatically lead to reports of low quality or invalid assessment of benefit‐risk. However, in depth knowledge of statistical methodology is often necessary to uncover weaknesses and potentially biased efficacy estimates. This might be of importance for the final opinion on granting a marketing authorization, and statistical review should therefore be conducted by those who are professionally expert in the area. A positive trend toward an increased involvement of statistical expertise in the European network of regulatory agencies is observed. Copyright © 2009 John Wiley & Sons, Ltd.     

Issues in applying recent CPMP ‘Points to Consider’ and FDA guidance documents with biostatistical implications

The International Conference on Harmonisation guideline ‘Statistical Principles for Clinical Trials’ was adopted by the Committee for Proprietary Medicinal Products (CPMP) in March 1998, and consequently is operational in Europe. Since then more detailed guidance on selected topics has been issued by the CPMP in the form of ‘Points to Consider’ documents. The intent of these was to give guidance particularly to non‐statistical reviewers within regulatory authorities, although of course they also provide a good source of information for pharmaceutical industry statisticians. In addition, the Food and Drug Administration has recently issued a draft guideline on data monitoring committees. In November 2002 a one‐day discussion forum was held in London by Statisticians in the Pharmaceutical Industry (PSI). The aim of the meeting was to discuss how statisticians were responding to some of the issues covered in these new guidelines, and to document consensus views where they existed. The forum was attended by industry, academic and regulatory statisticians. This paper outlines the questions raised, resulting discussions and consensus views reached. It is clear from the guidelines and discussions at the workshop that the statistical analysis strategy must be planned during the design phase of a clinical trial and carefully documented. Once the study is complete the analysis strategy should be thoughtfully executed and the findings reported. Copyright © 2003 John Wiley & Sons, Ltd.     

Ideas of statistical experts on the choice of an analysis method

The process of data analysis can be divided into stages. The opinions of 20 statisticians on the considerations that are relevant to this decision have been studied. Nineteen concepts were identified which can be classijied into five groups:the analysis question; characteristics of the data collection; characteristics of the data; conditions for and influences on data analysis; conditions for and influences on statistical consultation. Economists mention considerations different to those mentioned by social scientists. Together the considerations form an exhaustive list of concepts that are relevant to the design of computerized support in statistics.     

Communication of statistcal concepts: examples in medical collaboration

While effective communication of statistical concepts is important for the enthusiastic adoption of these concepts by collaborators, statisticians are not necessarily trained in the process of communication with collaborators in other substantive fields. It is proposed that increased attention be paid to pedagogical techniques for communicating to our non-statistical colleagues what statisticians have to offer to the design and analysis aspects of a collaborative effort. One approach is to offer examples relevant to our colleagues’ fields when we explain statistical ideas. This paper provides several such examples from the field of neurology, focusing on the issue of sample selection bias and prospective study designs.     

基于内部民调的地方统计数据准确性及影响因素研究

当前作为衡量经济和社会发展状况的统计数据的准确性已成为社会大众关注的焦点问题之一。以政府统计工作者为对象调查其对地方统计数据准确性及影响因素的判断,结果表明:当前中国各地统计数据质量总体比较可靠,但是一些地区统计指标的数据准确性较低,"水分"较大,领导干预是影响统计数据质量第一因素。     

网络技术下统计的变革和统计教育面临的任务

网络经济的发展使现行的统计信息生产方式和统计制度发生深刻变革,使统计人才的知识结构发生重大变化,从而对统计教育的着力点和培养目标、培养方式提出了新的要求。如何培养大量优秀的复合型统计人才,极大地提高统计人员的素质,是统计教育面临的艰巨任务。     

Who wants to be an ICH Euro billionaire?

The ICH E9 guideline on Statistical Principles for Clinical Trials is a pivotal document for statisticians in clinical research in the pharmaceutical industry guiding, as it does, statistical aspects of the planning, conduct and analysis of regulatory clinical trials. New statisticians joining the industry require a thorough and lasting understanding of the 39-page guideline. Given the amount of detail to be covered, traditional (lecture-style) training methods are largely ineffective. Directed reading, perhaps in groups, may be a helpful approach, especially if experienced staff are involved in the discussions. However, as in many training scenarios, exercise-based training is often the most effective approach to learning. In this paper, we describe several variants of a training module in ICH E9 for new statisticians, combining directed reading with a game-based exercise, which have proved to be highly effective and enjoyable for course participants.     

Professional development of statisticians in the pharmaceutical sector: evolution over the past decade and into the future

The adoption of The International Conference on Harmonization Tripartite Guideline: Statistical Principles for Clinical Trials (ICH-E9) has provided a foundation for the application of statistical principles in clinical research and raised awareness of the value of a statistical contribution to the wider pharmaceutical R&D process. In addition, over the past decade globalization of the pharmaceutical R&D process and the measures taken to address reduced productivity and spiralling costs have impacted on the roles and career opportunities for statisticians working in the pharmaceutical sector. This has enhanced the need for continuing professional development to equip statisticians with the skills to fully contribute to creating innovative solutions. In the future, key areas of focus are the establishment of professional standards for statistical work and increasing the collaboration between statisticians working in industry, regulatory agencies and academia. In addition, the diversity of roles and potential career paths for statisticians embarking on a career in the pharmaceutical sector emphasizes the importance of mentoring and coaching. For the more experienced statisticians, there are unprecedented opportunities to lead and innovate.     

企业统计数据质量影响因素的实证分析

为明确企业统计数据质量的影响因素,定量描述各因素之间的关系,利用SEM模型,通过SPSS AMOS18.0软件进行数据分析,得到企业的信息化程度、企业重视化程度、企业统计力量、统计人员知识水平、统计人员地位、组织正规化程度6个因素的企业统计数据质量结构模型,并比较各个因素对企业统计数据质量影响的大小及各影响因素之间的相关关系,为进一步提高企业的统计数据工作提供了依据。     

The statistician's role in the prevention of missing data

Considerable statistical research has been performed in recent years to develop sophisticated statistical methods for handling missing data and dropouts in the analysis of clinical trial data. However, if statisticians and other study team members proactively set out at the trial initiation stage to assess the impact of missing data and investigate ways to reduce dropouts, there is considerable potential to improve the clarity and quality of trial results and also increase efficiency. This paper presents a Human Immunodeficiency Virus (HIV) case study where statisticians led a project to reduce dropouts. The first step was to perform a pooled analysis of past HIV trials investigating which patient subgroups are more likely to drop out. The second step was to educate internal and external trial staff at all levels about the patient types more likely to dropout, and the impact this has on data quality and sample sizes required. The final step was to work collaboratively with clinical trial teams to create proactive plans regarding focused retention efforts, identifying ways to increase retention particularly in patients most at risk. It is acknowledged that identifying the specific impact of new patient retention efforts/tools is difficult because patient retention can be influenced by overall study design, investigational product tolerability profile, current standard of care and treatment access for the disease under study, which may vary over time. However, the implementation of new retention strategies and efforts within clinical trial teams attests to the influence of the analyses described in this case study. Copyright © 2012 John Wiley & Sons, Ltd.     

Statistical problems in environmental research

Growing concern about the health effects of exposure to pollutants and other chemicals in the environment has stimulated new research to detect and quantify environmental hazards. This research has generated many interesting and challenging methodological problems for statisticians. One type of statistical research develops new methods for the design and analysis of individual studies. Because current research of this type is too diverse to summarize in a single article, we discuss current work in two areas of application: the carcinogen bioassay in small rodents and epidemiologic studies of air pollution. To assess the risk of a potentially harmful agent, one must frequently combine evidence from different and often quite dissimilar studies. Hence, this paper also discusses the central role of data synthesis in risk assessment, reviews some of the relevant statistical literature, and considers the role of statisticians in evaluating and combining evidence from diverse sources.     

Massively parallel computing: a statistical application

Massively parallel computing is a computing environment with thousands of subprocessors. It requires some special programming methods, but is well suited to certain imaging problems. One such statistical example is discussed in this paper. In addition there are other natural statistical problems for which this technology is well suited. This paper describes our experience, as statisticians, with a massively parallel computer in a problem of image correlation spectroscopy. Even with this computing environment some direct computations would still take in the order of a year to finish. It is shown that some of the algorithms of interest can be made parallel.     

Preparing Statisticians for Careers in Industry: Report of the ASA Section on Statistical Education Committee on Training of Statisticians for Industry

This report provides guidelines for universities to consider in developing programs for training statisticians who will work in industry. Useful information for students who are considering industrial employment is also included. The recommended programs focus on real problems and the statistical theory and methodology that are useful in their solution. Technical competence is only one of many factors that industry considers when hiring and promoting statisticians. When a statistician leaves school, his or her skills and experiences should include statistical knowledge, practical problem solving, consulting practice, and the ability to communicate orally and in writing with nonstatisticians. There are many details that must be worked out (e.g., content of specific courses and organization of consulting internship programs), and it is hoped that the statistical societies and universities will form committees, hold conferences, and develop programs to address these issues further. Many of our recommendations apply more broadly to the training of all types of practicing statisticians.     

The Future of Statistical Computing on Desktop Computers

A class of computing devices known as desktop computers has emerged over the last several years. The International Data Corporation (McGovern 1980) estimates that the number of desktop computers is increasing by approximately 53,000 each month. Because of the projected widespread use of desktop computers and anticipated improvements in hardware, the potential for impressive statistical computing on these devices is exciting. Two features of desktop computers will be particularly important for those doing statistical analyses: (a) the ease-of-use of the computers, and (b) their extensive graphics capabilities. The author suggests that sophisticated statistical software will be available in the near future on many different models of desktop computers. Indeed, several of the manufacturers provide high-quality software at the present time. The implications for statisticians of a rapid growth rate for desktop computers are discussed for data analysis, software development, graphics, and instructional usage.     

大数据时代统计学的重构与创新

本文集中介绍了多位顶尖统计学家在大数据研究方面的新进展,内容涉及大数据背景下政府统计需求,统计设计,统计学理论框架的重构,统计学利用大数据在基因学、天文学、宇宙学、流行病学、经济金融学、生命科学和工程学等领域中的应用,以及大数据人才培养问题等。     

Subgroup analyses of clinical effectiveness to support health technology assessments

Subgroup analysis is an integral part of access and reimbursement dossiers, in particular health technology assessment (HTA), and their HTA recommendations are often limited to subpopulations. HTA recommendations for subpopulations are not always clear and without controversies. In this paper, we review several HTA guidelines regarding subgroup analyses. We describe good statistical principles for subgroup analyses of clinical effectiveness to support HTAs and include case examples where HTA recommendations were given to subpopulations only. Unlike regulatory submissions, pharmaceutical statisticians in most companies have had limited involvement in the planning, design and preparation of HTA/payers submissions. We hope to change this by highlighting how pharmaceutical statisticians should contribute to payers' submissions. This includes early engagement in reimbursement strategy discussions to influence the design, analysis and interpretation of phase III randomized clinical trials as well as meta-analyses/network meta-analyses. The focus on this paper is on subgroup analyses relating to clinical effectiveness as we believe this is the first key step of statistical involvement and influence in the preparation of HTA and reimbursement submissions.