Bøger i Statistics in Practice serien

Offers guidance to forensic scientists with little dependence on mathematical ability. This book helps to assess DNA evidence and present that evidence in a courtroom setting.

This essential guide on subgroup analyses in the emerging area of personalized medicine covers the issues of subgroup analyses from a practical and a theoretical/methodological point of view. The practical part introduces the issues using examples from the literature where subgroup analyses led to unexpected or difficult-to-interpret results, which have been interpreted differently by different stakeholders. On the technical side, the book addresses selection and selection bias variance reduction by borrowing information from the full population in estimating a subgroup effect. To this end, subgroup analysis will be linked to statistical modelling, and subgroup selection to model selection. This connection makes the techniques developed for model selection applicable to subgroup analysis. Beginning with a history of subgroup analysis, Exploratory Subgroup Analyses in Clinical Research offers chapters that cover: objectives and current practice of subgroup analyses; pitfalls of subgroup analyses; subgroup analysis and modeling; hierarchical models in subgroup analysis; and selection bias in regression. It also looks at the predicted individual treatment effect and offers an outlook of the topic in its final chapter. Focuses on the statistical aspects of subgroup analysis Filled with classroom and conference-workshop tested material Written by a leading expert in the field of subgroup analysis Complemented with a companion website featuring downloadable datasets and examples for teaching use Exploratory Subgroup Analyses in Clinical Research is an ideal book for medical statisticians and biostatisticians and will greatly benefit physicians and researchers interested in personalized medicine.

Statistical Monitoring of Complex Multivariate Processes summarizes recent advances in statistical-based process monitoring of complex multivariate process systems. The book includes a broad range of applications of multivariate statistical techniques into the area of mechanical, manufacturing, and power engineering.

This book covers all the latest advances, as well as more established methods, in the application of statistical and optimisation methods within modern industry. These include applications from a range of industries that include micro-electronics, chemical, automotive, engineering, food, component assembly, household goods and plastics.

The need to understand, interpret and analyse competing risk data is key to many areas of science, particularly medical research.

A mixed model allows the incorporation of both fixed and random variables within a statistical analysis. This enables efficient inferences and more information to be gained from the data. The application of mixed models is an increasingly popular way of analysing medical data, particularly in the pharmaceutical industry.

This book provides an introduction to both Bayesian methods and gene expression, accessible to people with backgrounds in either. The text is enhanced by the inclusion of numerous problems and solutions, designed with an emphasis on methodology and application.

The statistical analysis of cost-effectiveness data is becoming increasingly important within health and medical research. Statistical Analysis of Cost-Effectiveness Data provides a practical book that synthesises the huge amount of research that has taken place in the area over the last two decades.

This text shows how stochastic geometry can be applied to real structural problems in materials science and technology. It pays particular attention to describing spatial sizes and shapes of grains and particles, developments in stochastic geometry, and relevant computer simulation techniques.

Dose-finding in practice is often done very poorly; conventional methods, which are in widespread use, can be unreliable and lead to inaccurate results. However, there have been many advances in recent years, with new sophisticated statistical techniques being developed. It is important that these new techniques are utilized correctly.

A state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of finance The use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance.

* This book provides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementations, with an emphasis on healthcare techniques. * Contains introductory explanations of Bayesian principles common to all areas.

Uncertain Judgments Eliciting Experts' Probabilities presents a range of tried and tested elicitation methods to enable statisticians to get make the most of expert opinion. An elicitation method forms a bridge between an expert's opinion and an expression of these points in a statistically useful form.

This text look at cross-over trials which are experiments in which subjects, whether patients or healthy volunteers, are each given a number of treatments with the object being to study the differences between these treatments. They are used extensively in clinical research.

READ ALL ABOUT IT! David Spiegelhalter has recently joined the ranks of Isaac Newton, Charles Darwin and Stephen Hawking by becoming a fellow of the Royal Society. Originating from the Medical Research Council's biostatistics unit, David has played a leading role in the Bristol heart surgery and Harold Shipman inquiries.

Statistical complex survey analysis is a means to analyse the results, and gain information about a large population based on a complex survey of a sample of that population. A complex survey is a sample survey that divides the population into subgroups and collecting information from clusters within each subgroup and combining the results.

Statistics and the Evaluation of Evidence for Forensic ScientistsThe leading resource in the statistical evaluation and interpretation of forensic evidenceThe third edition of Statistics and the Evaluation of Evidence for Forensic Scientists is fully updated to provide the latest research and developments in the use of statistical techniques to evaluate and interpret evidence. Courts are increasingly aware of the importance of proper evidence assessment when there is an element of uncertainty. Because of the increasing availability of data, the role of statistical and probabilistic reasoning is gaining a higher profile in criminal cases. That's why lawyers, forensic scientists, graduate students, and researchers will find this book an essential resource, one which explores how forensic evidence can be evaluated and interpreted statistically. It's written as an accessible source of information for all those with an interest in the evaluation and interpretation of forensic scientific evidence.* Discusses the entire chain of reasoning-from evidence pre-assessment to court presentation;* Includes material for the understanding of evidence interpretation for single and multiple trace evidence;* Provides real examples and data for improved understanding.Since the first edition of this book was published in 1995, this respected series has remained a leading resource in the statistical evaluation of forensic evidence. It shares knowledge from authors in the fields of statistics and forensic science who are international experts in the area of evidence evaluation and interpretation. This book helps people to deal with uncertainty related to scientific evidence and propositions. It introduces a method of reasoning that shows how to update beliefs coherently and to act rationally. In this edition, readers can find new information on the topics of elicitation, subjective probabilities, decision analysis, and cognitive bias, all discussed in a Bayesian framework.

Recent progress in fast, parallel computing and in simulation-based inference has lead to the development of extremely powerful statistical tools. These can now be successfully applied to address the most pressing practical and ethical concerns arising from medical decision problems.

Disease mapping involves the analysis of geo-referenced disease incidence data and has many applications, for example within resource allocation, cluster alarm analysis, and ecological studies. There is a real need amongst public health workers for simpler and more efficient tools for the analysis of geo-referenced disease incidence data.

Meta--analysis is one of the main statistical methods used in clinical trials. Previous accounts of meta--analysis have given the impression that the topic is a series of separate techniques. This book provides a unified approach, developing the subject from mathematical theory through to practical discussions of implementation.

Covers practical and fundamental aspects of environmental statistics.

Selection bias can, and does, occur, even in randomized clinical trials. Steps need to be taken in order to ensure that this does not compromise the integrity of clinical trials; hence "Selection Bias and Covariate Imbalances in Randomized Clinical Trials" offers a comprehensive treatment of the subject and the methodology involved.

Challenges arising from changes in social and political life, in technology and in education are stimulating debate in the statistical community.

There has been substantial growth in the use of data monitoring committees in recent years, particularly within the pharmaceutical industry. This growth has brought with it increasing uncertainty regarding regulatory compliance, and the statistician or clinical trials co-ordinator often has to struggle with conflicting information.

Modeling and Analysis of Compositional Data presents a practical and comprehensive introduction to the analysis of compositional data along with numerous examples to illustrate both theory and application of each method.

Introduces risk assessment with key theories, proven methods, and state-of-the-art applications Risk Assessment: Theory, Methods, and Applications remains one of the few textbooks to address current risk analysis and risk assessment with an emphasis on the possibility of sudden, major accidents across various areas of practice--from machinery and manufacturing processes to nuclear power plants and transportation systems. Updated to align with ISO 31000 and other amended standards, this all-new 2nd Edition discusses the main ideas and techniques for assessing risk today. The book begins with an introduction of risk analysis, assessment, and management, and includes a new section on the history of risk analysis. It covers hazards and threats, how to measure and evaluate risk, and risk management. It also adds new sections on risk governance and risk-informed decision making; combining accident theories and criteria for evaluating data sources; and subjective probabilities. The risk assessment process is covered, as are how to establish context; planning and preparing; and identification, analysis, and evaluation of risk. Risk Assessment also offers new coverage of safe job analysis and semi-quantitative methods, and it discusses barrier management and HRA methods for offshore application. Finally, it looks at dynamic risk analysis, security and life-cycle use of risk. Serves as a practical and modern guide to the current applications of risk analysis and assessment, supports key standards, and supplements legislation related to risk analysis Updated and revised to align with ISO 31000 Risk Management and other new standards and includes new chapters on security, dynamic risk analysis, as well as life-cycle use of risk analysis Provides in-depth coverage on hazard identification, methodologically outlining the steps for use of checklists, conducting preliminary hazard analysis, and job safety analysis Presents new coverage on the history of risk analysis, criteria for evaluating data sources, risk-informed decision making, subjective probabilities, semi-quantitative methods, and barrier management Contains more applications and examples, new and revised problems throughout, and detailed appendices that outline key terms and acronyms Supplemented with a book companion website containing Solutions to problems, presentation material and an Instructor Manual Risk Assessment: Theory, Methods, and Applications, Second Edition is ideal for courses on risk analysis/risk assessment and systems engineering at the upper-undergraduate and graduate levels. It is also an excellent reference and resource for engineers, researchers, consultants, and practitioners who carry out risk assessment techniques in their everyday work.

A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective.

A comprehensive and practical resource for analyses of crossover designs For ethical reasons, it is vital to keep the number of patients in a clinical trial as low as possible.

An authoritative introduction to efficiency and productivity analysis with applications in both the banking and finance industry In light of the recent global financial crisis, several studies have examined the efficiency of financial institutions.

Explores computer-intensive probability and statistics for ecosystem management decision making Simulation is an accessible way to explain probability and stochastic model behavior to beginners.