Bioterrorism: the statistical issues

Bioterrorism research has had an upsurge since the autumn of 2001. Elizabeth Halloran and Ira Longini describe particular contributions that statisticians and mathematical modellers can make to bioterrorism research related to infectious diseases. They argue that much can be learned from emerging infectious diseases that is applicable to potential bioterrorist threats.     

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.     

Time-sequential statistical procedures: a preface

This preface outlines the Scope of the time-sequential procedures considered in this special issue and presents some of the basic terminologies used in the subsequent papers.     

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.     

Sir Godfrey Thomson: a statistical pioneer

Summary.  Godfrey Thomson (1881–1955) was a leading figure in intelligence testing who made his name in that field first at Armstrong College, Newcastle, and then at the University of Edinburgh. In the course of his practical work he identified many theoretical problems which were essentially statistical in character. In particular, he used maximum likelihood estimation as early as 1919 and his statistical work largely set the course of modern factor analysis and related techniques. His statistical abilities were recognized, at different stages of his career, by both Karl Pearson and Sir Ronald Fisher. His key insight was to recognize the importance of Fisherian inference for the future of that subject.     

The mystery of the lost star: A statistical detective story

In July 2005 the Healthcare Commission released its annual "star ratings" for English National Health Service (NHS) trusts¹, in which acute or specialist hospitals, mental health services, ambulance services and primary care trusts were each given 0, 1, 2 or 3 stars. There was some surprise that the Cambridge University Hospitals NHS Foundation Trust (better known as Addenbrooke's Hospital) dropped from the 3 stars obtained in 2004 to 2 stars. David Spiegelhalter investigated .     

Statistics development: statistical methods meeting the user’s needs

Statistical methods have the potential of being effectively used by industrial practitioners if they satisfied two criteria: functionality and usability. Statistical methods are usually the product of statistical research activities of universities and other research organizations. Some already satisfy these criteria; however, many do not. The effect is that potentially relevant methods are not used in practice as often as they could be. In this paper we will present an approach regarding ‘statistics development,’ in which the end-user is given a central position, so that the results from statistical research aim to meet the needs and requirements of the practitioner. Examples of known and new methods will be presented, and we will discuss issues such as education in statistics, the link with statistical consultancy and publication of methods through various channels.     

Aggregate statistical data: models for their representation

The paper gives a review of a number of data models for aggregate statistical data which have appeared in the computer science literature in the last ten years.After a brief introduction to the data model in general, the fundamental concepts of statistical data are introduced. These are called statistical objects because they are complex data structures (vectors, matrices, relations, time series, etc) which may have different possible representations (e.g. tables, relations, vectors, pie-charts, bar-charts, graphs, and so on). For this reason a statistical object is defined by two different types of attribute (a summary attribute, with its own summary type and with its own instances, called summary data, and the set of category attributes, which describe the summary attribute). Some conceptual models of statistical data (CSM, SDM4S), some semantic models of statistical data (SCM, SAM*, OSAM*), and some graphical models of statistical data (SUBJECT, GRASS, STORM) are also discussed.     

Illness-death model: statistical perspective and differential equations

The aim of this work is to relate the theory of stochastic processes with the differential equations associated with multistate (compartment) models. We show that the Kolmogorov Forward Differential Equations can be used to derive a relation between the prevalence and the transition rates in the illness-death model. Then, we prove mathematical well-definedness and epidemiological meaningfulness of the prevalence of the disease. As an application, we derive the incidence of diabetes from a series of cross-sections.     

Review of the Stata statistical package

Statistics and Computing -     

Evaluation of the statistical power for multiple tests: a case study

It is challenging to estimate the statistical power when a complicated testing strategy is used to adjust for the type-I error for multiple comparisons in a clinical trial. In this paper, we use the Bonferroni Inequality to estimate the lower bound of the statistical power assuming that test statistics are approximately normally distributed and the correlation structure among test statistics is unknown or only partially known. The method was applied to the design of a clinical study for sample size and statistical power estimation.     

Shipman's statistical legacy

Harold Shipman, who in January committed suicide in prison, has become notorious the world over as one of the most prolific serial killers of all time. His case has also seriously dented public confidence in doctors. David Spiegelhalter and Nicky Best explain how industrial quality control techniques could be adapted to signal when death rates among a doctor's patients are surprisingly high, and the tricky issues that would arise in implementing such a monitoring system.