A Unified Approach of Meta-Analysis: Application to an Antecedent Biomarker Study in Alzheimer's Disease

This article provides a unified methodology of meta-analysis that synthesizes medical evidence by using both available individual patient data (IPD) and published summary statistics within the framework of likelihood principle. Most up-to-date scientific evidence on medicine is crucial information not only to consumers but also to decision makers, and can only be obtained when existing evidence from the literature and the most recent individual patient data are optimally synthesized. We propose a general linear mixed effects model to conduct meta-analyses when individual patient data are only available for some of the studies and summary statistics have to be used for the rest of the studies. Our approach includes both the traditional meta-analyses in which only summary statistics are available for all studies and the other extreme case in which individual patient data are available for all studies as special examples. We implement the proposed model with statistical procedures from standard computing packages. We provide measures of heterogeneity based on the proposed model. Finally, we demonstrate the proposed methodology through a real life example studying the cerebrospinal fluid biomarkers to identify individuals with high risk of developing Alzheimer's disease when they are still cognitively normal.     

Key Attributes of a Modern Statistical Computing Tool

ABSTRACT

In the 1990s, statisticians began thinking in a principled way about how computation could better support the learning and doing of statistics. Since then, the pace of software development has accelerated, advancements in computing and data science have moved the goalposts, and it is time to reassess. Software continues to be developed to help do and learn statistics, but there is little critical evaluation of the resulting tools, and no accepted framework with which to critique them. This article presents a set of attributes necessary for a modern statistical computing tool. The framework was designed to be broadly applicable to both novice and expert users, with a particular focus on making more supportive statistical computing environments. A modern statistical computing tool should be accessible, provide easy entry, privilege data as a first-order object, support exploratory and confirmatory analysis, allow for flexible plot creation, support randomization, be interactive, include inherent documentation, support narrative, publishing, and reproducibility, and be flexible to extensions. Ideally, all these attributes could be incorporated into one tool, supporting users at all levels, but a more reasonable goal is for tools designed for novices and professionals to “reach across the gap,” taking inspiration from each others’ strengths.     

STATISTICS: REFLECTIONS ON THE PAST AND VISIONS FOR THE FUTURE

Statistics as data is ancient, but as a discipline of study and research it has a short history. Courses leading to degrees in statistics have been introduced in universities some sixty to seventy years ago. They were not considered to constitute a basic discipline with a subject matter of its own. However, during the last seventy five years, it has developed as a powerful blend of science, technology and art for solving problems in all areas of human endeavor. Now-a-days statistics is used in scientific research, economic development through optimum use of resources, increasing industrial productivity, medical diagnosis, legal practice, disputed authorship, and optimum decision making at individual and institutional levels. What is the future of statistics in the coming millennium dominated by information technology encompassing the whole of communications, interaction with intelligent systems, massive data bases, and complex information processing networks? The current statistical methodology based on probabilistic models applied on small data sets appears to be inadequate to meet the needs of the society in terms of quick processing of data and making the information available for practical purposes. Adhoc methods are being put forward under the title Data Mining by computer scientists and engineers to meet the needs of customers. The paper reviews the current state of the art in statistics and discusses possible future developments considering the availability of large data sets, enormous computing power and efficient optimization techniques using genetic algorithms and neural networks.

     

Decision‐making in drug development using a composite definition of success

Evidence‐based quantitative methodologies have been proposed to inform decision‐making in drug development, such as metrics to make go/no‐go decisions or predictions of success, identified with statistical significance of future clinical trials. While these methodologies appropriately address some critical questions on the potential of a drug, they either consider the past evidence without predicting the outcome of the future trials or focus only on efficacy, failing to account for the multifaceted aspects of a successful drug development. As quantitative benefit‐risk assessments could enhance decision‐making, we propose a more comprehensive approach using a composite definition of success based not only on the statistical significance of the treatment effect on the primary endpoint but also on its clinical relevance and on a favorable benefit‐risk balance in the next pivotal studies. For one drug, we can thus study several development strategies before starting the pivotal trials by comparing their predictive probability of success. The predictions are based on the available evidence from the previous trials, to which new hypotheses on the future development could be added. The resulting predictive probability of composite success provides a useful summary to support the discussions of the decision‐makers. We present a fictive, but realistic, example in major depressive disorder inspired by a real decision‐making case.     

Statistical Computing Packages: Some Words of Caution

Three situations are cited when caution is needed in using statistical computing packages: (a) when analyzing data and having insufficient statistical knowledge to completely understand the output; (b) when teaching the use of packages in a statistics course, to the exclusion of teaching statistics; and (c) when using packages in subject-matter teaching, without teaching the statistical methods underlying the packages.     

A Study of Student Reaction to the Use of Minitab in an Introductory Statistics Course

Traditionally, the introductory statistics course, Principles of Statistics (STAT 101), at Iowa State University has been taught without reference to a statistical analysis computing package. Although important for the implementation of statistical techniques, a computer component has been perceived by instructors to take time away from the coverage of statistical topics. To gauge students' reactions to the usefulness of a statistical computing package, an experiment was conducted during the fall term of 1986. Volunteers from a STAT 101 class were randomly assigned to either a control group or a computer use group. Both groups filled out questionnaires at the beginning and end of the semester. During the semester, the computer use group had access to and instruction in the use of Minitab. This instruction was tied to homework and laboratory assignments for the course. This article presents results of this experiment. On the basis of the responses to the questionnaires, the value of a statistical computing package as a pedagogical tool is examined. Recommendations for the use of a statistical computing package in a large introductory statistics course are made.     

关于AHP统计构权方法的几点看法

在多指标统计综合评价中,权数是影响评价结论的一个重要因素。不同的权数体系有可能导致不同的评价结论。最近几年来,人们指出了不少构造统计权数的方法。其中行之有效的构权方法当首推AHP构权法与DELPHI构权法。本文拟就AHP构权法谈几点自己的看法。     

小型经济单位从业人员调查抽样方法研究

不执行统计报表制度的小型经济单位的从业人员统计,应当用抽样调查方法进行。小型经济单位的各种统计调查项目,其中如生产统计调查项目、经营统计调查项目、劳动统计调查项目等等,应当合并在一起并分行业进行抽样调查。对小型工业单位进行从业人员调查的抽样技术,包括:样本轮换方针、在样本轮换条件下如何构造估计量、怎样对估计量的方差进行估计等。     

Some Remarks on Statistical Education

A definition of the subject of statistics is given, and the difference between the chalkboard world of the teacher of statistics and the real world of the experimenter is stressed. An overemphasis on significance testing, hypothesis testing, and decision procedures has led to a de-emphasis of statistical design. The teaching of statistical design theory, statistics teaching in a changing world, the importance of model building, and different approaches to teaching statistics are discussed. Some published materials developed to meet teaching needs and a new type of statistics course are described. Information about special issues in statistical education (teaching and consulting) is presented.     

建立中国统计业务流程的构想

 规范的统计业务流程是保证统计数据生产标准化,提高生产过程的透明度,提高统计数据质量的基本保障。通用统计业务流程模型是由联合国欧洲经济委员会等国际组织经过多年研究,为统计机构提供一个标准专业术语的协议基础,是描述和定义生产官方统计数据的业务流程。中国企业一套表改革的核心是重构统计业务流程,通过建立企业一套表工作业务流程提高了统计工作标准化、规范化。本文通过评价企业一套表工作业务流程,在与国际通用统计业务流程模型进行比较的基础上,借鉴其他国家的实践经验,研究提出建立中国统计业务流程的构想,为提高中国统计工作的标准化、规范化做一探索。     

Introductory Statistics Textbooks and the GAISE Recommendations

The six recommendations made by the Guidelines for Assessment and Instruction in Statistics Education (GAISE) committee were first communicated in 2005 and more formally in 2010. In this article, 25 introductory statistics textbooks are examined to assess how well these textbooks have incorporated the three GAISE recommendations most relevant to implementation in textbooks (statistical literacy and thinking; use of real data; stress concepts over procedures). The implementation of another recommendation (using technology) is described but not assessed. In general, most textbooks appear to be adopting the GAISE recommendations reasonably well in both exposition and exercises. The textbooks are particularly adept at using real data, using real data well, and promoting statistical literacy. Textbooks are less adept—but still rated reasonably well, in general—at explaining concepts over procedures and promoting statistical thinking. In contrast, few textbooks have easy-usable glossaries of statistical terms to assist with understanding of statistical language and literacy development. Supplementary materials for this article are available online.     

统计数据开发的混沌思考

 统计学是研究随机现象统计规律性的学科。贝叶斯学派认为是：“以样本推断总体的艺术”。统计数据作为样本的数量反映,同时具有随机性和确定性的双重意义。混沌则是“确定性的随机性”（福特语）,“是有序与无序都很强烈时形成的动力学”（苗东升语）。可见,统计学与混沌学有着天然的“缘分”,本文呼唤统计学界同仁,注意到如下实际：混沌理论的创立,是继相对论和量子力学问世以来,对人类整个知识体系的又一次巨大冲击,是20世纪数理科学的第三次革命,正如格莱克在他的《混沌：开创新学科》一书中所说：“混沌开始之处,经典科学就终止了”。在统计分析中,特别是数据开发时应留给混沌理论一定的空间。、     

Enhancing statistical education by using role-plays of consultations

Summary.  Role-plays in which students act as clients and statistical consultants to each other in pairs have proved to be an effective class exercise. As well as helping to teach statistical methodology, they are effective at encouraging statistical thinking, problem solving, the use of context in applied statistical problems and improving attitudes towards statistics and the statistics profession. Furthermore, they are fun. This paper explores the advantages of using role-plays and provides some empirical evidence supporting their success. The paper argues that there is a place for teaching statistical consulting skills well before the traditional post-graduate qualification in statistics, including to school students with no knowledge of techniques in statistical inference.     

Teaching Statistical Consulting Before Statistical Methodology

This paper outlines and discusses the advantages of an ‘Introduction to Statistical Consulting’ course (ISC) that exposes students to statistical consulting early in their studies. The course is intended for students before, or while, they study their units in statistical techniques, and assumes only a first‐year introductory statistics unit. The course exposes undergraduate students to the application of statistics and helps develop statistical thinking. An important goal is to introduce students to work as a statistician early in their studies because this motivates some students to study statistics further and provides a framework to motivate the learning of further statistical techniques. The ISC has proved popular with students, and this paper discusses the reasons for this popularity and the benefits of an ISC to statistical education and the statistics profession.     

统计专业的新观念

The article discusses the phenomenon that statistical profession is not paid great attention to and even not understood by the public. Through some examples of social activity, teaching and statistical application the author proposes some measures and thinking that can take to improve public awareness to the cause of statistics through three forms of efforts including changing the public’s sense of statistics, actively spreading the techniques of applied statistics and strengthening propaganda to statistics.     

企业统计市场化定位的目标取向——再论企业统计改革

一、对企业统计和企业统计改革的反思　　近年来 ,为了满足企业对市场信息的需求 ,学术界及统计工作人员对企业统计的改革提出了很多建设性意见 ,其共同点都是在维护企业统计的前提下 ,对企业统计提出了越来越高的要求。但笔者认为 ,目前企业统计人员面临的局面越来越尴尬 ,企业统计有不断削弱的趋势。因此 ,不能不对企业统计和企业统计改革有关问题提出反思。(一 )企业统计不应该是行政记录统计的原始定义应该是社会经济总体现象数量方面的调查研究活动。西方发达国家在市场经济条件下形成的关于统计的概念与我国长期以来在高度集中的计划…     

A review of parallel processing for statistical computation

Parallel computers differ from conventional serial computers in that they can, in a variety of ways, perform more than one operation at a time. Parallel processing, the application of parallel computers, has been successfully utilized in many fields of science and technology. The purpose of this paper is to review efforts to use parallel processing for statistical computing. We present some technical background, followed by a review of the literature that relates parallel computing to statistics. The review material focuses explicitly on statistical methods and applications, rather than on conventional mathematical techniques. Thus, most of the review material is drawn from statistics publications. We conclude by discussing the nature of the review material and considering some possibilities for the future.     

Statistical Computing: History and Trends

The evolution of computers is currently in a period of rapid change, stimulated by radically cheaper and smaller devices for processing and memory. These changes are certain to provide major opportunities and challenges for the use of computers in statistics. This article looks at history and current trends, in both general computing and statistical computing, with the goal of identifying key features and requirements for the near future. A discussion of the S language developed at Bell Laboratories illustrates some program design principles that can make future work on statistical programs more effective and more valuable.     

Global benefit-risk assessment in designing clinical trials and some statistical considerations of the method

When characterizing a therapy, the efficacy and the safety are two major aspects under consideration. In prescribing a therapy to a patient, a clinician puts the two aspects together and makes a decision based on a consolidated thought process. The global benefit-risk (GBR) measures proposed by Chuang-Stein et al. (Stat. Med. 1991; 10:1349-1359) are useful in facilitating the thinking, and creating the framework for making statistical comparisons based on benefit-risk point of view. This article describes how a GBR linear score was defined and used as the primary outcome measure in a clinical trial design. The robustness of the definitions of 'benefit' and 'risk' are evaluated using different criteria. The sensitivity of the pre-specified weights is also analyzed using alternative weights; one of those was determined by the relative to an identified distribution integral transformation approach (Biometrics 1958; 14:18-38). Statistical considerations are illustrated using pooled data from clinical trials studying antidepressant. The pros and cons for using GBR assessments in the setting of clinical trials are discussed.     

Official statistics, public policy and public trust

Summary.  The question of public confidence in official statistics has been central to government statistical policy for the last 10 years. This year the Statistics and Registration Service Act 2007 was passed. The paper suggests key characteristics of the new arrangements that will be needed if public confidence in the official statistics outputs is to be strengthened. It is argued that this will depend on public confidence in the statistical system as a whole rather than just the new Board. The organizational structure of the UK statistical system is described and this is linked to the issue of public confidence. Finally the wider questions of evidence-based policy and the use of statistics and statistical thinking throughout government are discussed.