Thanks to enormous funding for educational programs, the whole world ?knows? that HIV causes AIDS. But is what we know compatible with the facts? This book challenges the conventional wisdom on this issue. Collating and analyzing, for the first time, the results of more than two decades of HIV testing, it reveals that the common assumptions about HIV and AIDS are incompatible with the published data. Among the many topics explored are the failings of HIV testing, statistical evidence that HIV is neither sexually transmitted nor increasingly prevalent, and problems caused by the differing diagnostic criteria for AIDS around the world. But how could everyone have been so wrong for so long? This vital question, unaddressed in previous works questioning the HIV-AIDS connection, is central to this book. The author considers comparable missteps of modern science, and discusses how funding influences discovery in today's scientific circles.

The field of molecular evolution has experienced explosive growth in recent years due to the rapid accumulation of genetic sequence data, continuous improvements to computer hardware and software, and the development of sophisticated analytical methods. The increasing availability of large genomic data sets requires powerful statistical methods to analyse and interpret them, generating both computational and conceptual challenges for the field.
Computational Molecular Evolution provides an up-to-date and comprehensive coverage of modern statistical and computational methods used in molecular evolutionary analysis, such as maximum likelihood and Bayesian statistics. Yang describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of molecular sequence data, with a view to furthering our understanding of the evolution of genes and genomes. The book emphasizes essential concepts rather than mathematical proofs. It includes detailed derivations and implementation details, as well as numerous illustrations, worked examples, and exercises. It will be of relevance and use to students and professional researchers (both empiricists and theoreticians) in the fields of molecular phylogenetics, evolutionary biology, population genetics, mathematics, statistics and computer science. Biologists who have used phylogenetic software programs to analyze their own data will find the book particularly rewarding, although it should appeal to anyone seeking an authoritative overview of this exciting area of computational biology.

Emphasis on concepts rather than formulas Includes interesting examples with real data Uses Stata and R

Randomization, Masking, and Allocation Concealment is indispensable for any trial researcher who wants to use state of the art randomization methods, and also wants to be able to describe these methods correctly. Far too often the subtle nuances that distinguish proper randomization from flawed randomization are completely ignored in trial reports that state only that randomization was used, with no additional information. Experience has shown that in many cases, the type of randomization that was used was flawed. It is only a matter of time before medical journals and regulatory agencies come to realize that we can no longer rely on (or publish) flawed trials, and that flawed randomization in and of itself disqualifies a trial from being robust or high quality, even if that trial is of high quality otherwise. This book will help to clarify the role randomization plays in ensuring internal validity, and in drawing valid inferences from the data. The various chapters cover a variety of randomization methods, and are not limited to the most common (and most flawed) ones. Readers will come away with a profound understanding of what constitutes a valid randomization procedure, so that they can distinguish the valid from the flawed among not only existing methods but also methods yet to be developed.

Biosimilars have the potential to change the way we think about, identify, and manage health problems. They are already impacting both clinical research and patient care, and this impact will only grow as our understanding and technologies improve. Written by a team of experienced specialists in clinical development, this book discusses various potential drug development strategies, the design and analysis of pharmacokinetics (PK) studies, and the design and analysis of efficacy studies.

Guides You on the Development and Implementation of B-R Evaluations Benefit-Risk Assessment Methods in Medical Product Development: Bridging Qualitative and Quantitative Assessments provides general guidance and case studies to aid practitioners in selecting specific benefit-risk (B-R) frameworks and quantitative methods. Leading experts from industry, regulatory agencies, and academia present practical examples, lessons learned, and best practices that illustrate how to conduct structured B-R assessment in clinical development and regulatory submission. The first section of the book discusses the role of B-R assessments in medicine development and regulation, the need for both a common B-R framework and patient input into B-R decisions, and future directions. The second section focuses on legislative and regulatory policy initiatives as well as decisions made at the U.S. FDA's Center for Devices and Radiological Health. The third section examines key elements of B-R evaluations in a product's life cycle, such as uncertainty evaluation and quantification, quantifying patient B-R trade-off preferences, ways to identify subgroups with the best B-R profiles, and data sources used to assist B-R assessment. The fourth section equips practitioners with tools to conduct B-R evaluations, including assessment methodologies, a quantitative joint modeling and joint evaluation framework, and several visualization tools. The final section presents a rich collection of case studies. With top specialists sharing their in-depth knowledge, thought-provoking considerations, and practical advice, this book offers comprehensive coverage of B-R evaluation methods, tools, and case studies. It gives practitioners a much-needed toolkit to develop and conduct their own B-R evaluations.

Design and Analysis of Clinical Trials for Predictive Medicine provides statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics-from identifying molecular biomarkers using DNA microarrays to confirming their clinical utility in randomized clinical trials. The foundation of modern clinical trials was laid many years before modern developments in biotechnology and genomics. Drug development in many diseases is now shifting to molecularly targeted treatment. Confronted with such a major break in the evolution toward personalized or predictive medicine, the methodologies for design and analysis of clinical trials is now evolving. This book is one of the first attempts to contribute to this evolution by laying a foundation for the use of appropriate statistical designs and methods in future clinical trials for predictive medicine. It is a useful resource for clinical biostatisticians, researchers focusing on predictive medicine, clinical investigators, translational scientists, and graduate biostatistics students.

Analysis of Correlated Data with SAS and R: 4th edition presents an applied treatment of recently developed statistical models and methods for the analysis of hierarchical binary, count and continuous response data. It explains how to use procedures in SAS and packages in R for exploring data, fitting appropriate models, presenting programming codes and results. The book is designed for senior undergraduate and graduate students in the health sciences, epidemiology, statistics, and biostatistics as well as clinical researchers, and consulting statisticians who can apply the methods with their own data analyses. In each chapter a brief description of the foundations of statistical theory needed to understand the methods is given, thereafter the author illustrates the applicability of the techniques by providing sufficient number of examples. The last three chapters of the 4th edition contain introductory material on propensity score analysis, meta-analysis and the treatment of missing data using SAS and R. These topics were not covered in previous editions. The main reason is that there is an increasing demand by clinical researchers to have these topics covered at a reasonably understandable level of complexity. Mohamed Shoukri is principal scientist and professor of biostatistics at The National Biotechnology Center, King Faisal Specialist Hospital and Research Center and Al-Faisal University, Saudi Arabia. Professor Shoukri's research includes analytic epidemiology, analysis of hierarchical data, and clinical biostatistics. He is an associate editor of the 3Biotech journal, a Fellow of the Royal Statistical Society and an elected member of the International Statistical Institute.

Advance Praise for Forensic Cardiovascular Medicine "Using his vast experience in the medical-legal theater, Dr. RuDusky addresses a very complicated field in a simple and concise manner. Stressing the importance of honesty, integrity, and accuracy of data, he provides an insightful and interesting approach to the problems facing today's medical community." - John H. Ellis, IV, M.D., F.A.C.C., Chairman, Department of Cardiology, Wyoming Valley Healthcare System and Wilkes-Barre General Hospital "... a must-read for any new and training physician ... I now understand why Dr. RuDusky is considered to be a medical expert in his own right." - Damien M. Marycz, M.D., Internal Medicine Resident, Cleveland Clinic "Dr. RuDusky has always been fair, impartial, logical, and concise in his analysis ... This book adds significantly to a better understanding of the complex medicine behind his opinions." - Robert K. Randall, Prominent Midwest malpractice attorney "...this book is significant ... a major contribution for use by physicians, physicians' students, lawyers and judges connected with the field of forensic medicine in many different contexts." -Michael D. Schottland, Prominent East Coast malpractice attorney An Essential Text from a World-Renowned Expert in Cardiology A unique resource for medical examiners and forensic specialists, Forensic Cardiovascular Medicine draws upon Dr. Basil RuDusky's vast experience to provide coverage of the clinical aspects of cardiac disease in a forensic context. The book emphasizes some of the most frequently encountered cardiovascular medical problems facing the medical examiner or forensic medical specialist, while also placing special emphasis on those conditions and disease states that are apt to be overlooked, misdiagnosed, or tardily considered. Covers death certificates, autopsies, and the role of the medical examiner Presents 25 case studies from the author's experience to illustrate concepts, including cardiac trauma, vascular abnormalities, specific cardiopathic disorders, and toxic, physical, technical, epidemiological, and social influences Contains the first complete classification of myocardial contusion and blunt cardiac trauma Includes a special section on the cardiovascular effects of breast cancer therapy Dr. RuDusky has served as a consultant for the federal government, corporations, insurance companies, and independent medical service agencies. He sits on the manuscript review board for several medical journals and is associate editor of Angiology, the official international journal of the American Society of Angiology and the International Academy of Clinical and Applied Thrombosis/Hemostasis. In this volume, he brings his considerable expertise to this survey of the topic.

Spatial epidemiology is the description and analysis of the geographical distribution of disease. It is more important now than ever, with modern threats such as bio-terrorism making such analysis even more complex. This second edition of "Statistical Methods in Spatial Epidemiology" is updated and expanded to offer a complete coverage of the analysis and application of spatial statistical methods. The book is divided into two main sections: Part 1 introduces basic definitions and terminology, along with map construction and some basic models. This is expanded upon in Part II by applying this knowledge to the fundamental problems within spatial epidemiology, such as "disease mapping," "ecological analysis," "disease clustering," "bio-terrorism," "space-time analysis," "surveillance" and "infectious disease modelling," Provides a comprehensive overview of the main statistical methods used in spatial epidemiology. Updated to include a new emphasis on bio-terrorism and disease surveillance. Emphasizes the importance of space-time modelling and outlines the practical application of the method. Discusses the wide range of software available for analyzing spatial data, including WinBUGS, SaTScan and R, and features an accompanying website hosting related software. Contains numerous data sets, each representing a different approach to the analysis, and provides an insight into various modelling techniques.

This text is primarily aimed at medical statisticians, researchers and practitioners from public health and epidemiology. It is also suitable for postgraduate students of statistics and epidemiology, as well professionals working in government agencies.

In a global clinical development strategy, multiregional clinical trials (MRCTs) are vital in the development of innovative medicines. Multiregional Clinical Trials for Simultaneous Global New Drug Development presents a comprehensive overview on the current status of conducting MRCTs in clinical development. International experts from academia, industry, and health organizations address various aspects of the important problems in global clinical development and MRCTs. The book first provides a high-level introduction to the context, motivation, opportunities, and challenges in simultaneous global clinical development using MRCTs. It then focuses on the design, monitoring, and analysis/interpretation of MRCTs. The book concludes with an examination of the latest research topics from MRCT perspectives, such as special considerations by local health authorities, health economic evaluations, benefit-risk assessment, and medical devices. Explaining how to design, conduct, and interpret MRCTs, this book will help biostatisticians working in the late-stage clinical development of medical products. It will also be useful for statisticians and clinicians in the biopharmaceutical industry, regulatory agencies, and medical research institutes.

Review of the First Edition "The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully and does a nice job. I would highly recommend it ...The example-based approach is easy to follow and makes the book a very helpful desktop reference for many biostatistics methods."-Journal of Statistical Software Clinical Trial Data Analysis Using R and SAS, Second Edition provides a thorough presentation of biostatistical analyses of clinical trial data with step-by-step implementations using R and SAS. The book's practical, detailed approach draws on the authors' 30 years' experience in biostatistical research and clinical development. The authors develop step-by-step analysis code using appropriate R packages and functions and SAS PROCS, which enables readers to gain an understanding of the analysis methods and R and SAS implementation so that they can use these two popular software packages to analyze their own clinical trial data. What's New in the Second Edition Adds SAS programs along with the R programs for clinical trial data analysis. Updates all the statistical analysis with updated R packages. Includes correlated data analysis with multivariate analysis of variance. Applies R and SAS to clinical trial data from hypertension, duodenal ulcer, beta blockers, familial andenomatous polyposis, and breast cancer trials. Covers the biostatistical aspects of various clinical trials, including treatment comparisons, time-to-event endpoints, longitudinal clinical trials, and bioequivalence trials.

This work explains the purpose of statistical methods in medical studies and analyzes the statistical techniques used by clinical investigators, with special emphasis on studies published in "The New England Journal of Medicine". It clarifies fundamental concepts of statistical design and analysis, and facilitates the understanding of research results.

Absolute Risk: Methods and Applications in Clinical Management and Public Health provides theory and examples to demonstrate the importance of absolute risk in counseling patients, devising public health strategies, and clinical management. The book provides sufficient technical detail to allow statisticians, epidemiologists, and clinicians to build, test, and apply models of absolute risk. Features: Provides theoretical basis for modeling absolute risk, including competing risks and cause-specific and cumulative incidence regression Discusses various sampling designs for estimating absolute risk and criteria to evaluate models Provides details on statistical inference for the various sampling designs Discusses criteria for evaluating risk models and comparing risk models, including both general criteria and problem-specific expected losses in well-defined clinical and public health applications Describes many applications encompassing both disease prevention and prognosis, and ranging from counseling individual patients, to clinical decision making, to assessing the impact of risk-based public health strategies Discusses model updating, family-based designs, dynamic projections, and other topics Ruth M. Pfeiffer is a mathematical statistician and Fellow of the American Statistical Association, with interests in risk modeling, dimension reduction, and applications in epidemiology. She developed absolute risk models for breast cancer, colon cancer, melanoma, and second primary thyroid cancer following a childhood cancer diagnosis. Mitchell H. Gail developed the widely used "Gail model" for projecting the absolute risk of invasive breast cancer. He is a medical statistician with interests in statistical methods and applications in epidemiology and molecular medicine. He is a member of the National Academy of Medicine and former President of the American Statistical Association. Both are Senior Investigators in the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health.

Epidemiological studies show that cancer incidence is far more dependent on the conditions of life than previously supposed. Classically, cancers occurred with heavy exposure to a specific occupational hazard, or were associated with habits. In some instances, research shows, the incidence of cancer falls when the method of work or the associated habit is changed. In short, variation in incidence is now known to be the rule rather than the exception in cancer. No cancer that occurs with even moderate frequency, occurs everywhere and always to the same extent. Sometimes it is even epidemic, similar in scale to an epidemic of infectious disease, but modified by the fact that the induction period may be as much as thirty years.

Prevention of cancer is now coming to be regarded as a practicable alternative to its cure. We remain almost totally ignorant of how cancer is produced at the cellular level and, until we know this, our methods of prevention are liable to be cumbersome and inefficient. Ethical considerations and the time scale of the disease make it impossible to obtain experimental evidence in man and what action to take has been determined from observing nature's experiments and by analogy from experiments in animals.

The evidence from epidemiological studies is of particular interest. Such studies suggest relationships that would never be thought of in the ordinary course of laboratory work and results that are directly relevant to the problems of human disease. The large numbers at risk and the intensity of the medical care to which people with cancer are subjected, make it possible to recognize relatively small improvements. Such practical decisions, based on information thus obtained, have largely eliminated the risk of cancer due to occupational hazards in several industries.

"Richard Doll" (1912-2005) was a British psychologist and one of the most prominent epidemiologists of the twentieth century. Throughout out his research he was able to link smoking with health problems and was the first individual to link smoking with lung cancer and increased risk of heart disease. He also studies the relationship between asbestos and lung cancer and radiation and leukemia. He is the author of many books, including "The Causes of Cancer: Quantitative Estimates of Avoidable Risks of Cancer in the United States Today" and "Tobacco and Health."

Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips readers with skills to prepare health-related data in the proper format, process these data using relevant functions and software, and display the results as mapped or statistical summaries. Describing the wide range of available methods and key GIS concepts for spatial epidemiology, this book illustrates the utilities of the software using real-world data. Additional topics include geographic data models, address matching, geostatistical analysis, universal kriging, point pattern analysis, kernel density, spatio-temporal display, and disease surveillance.

Presenting a rare glimpse into the various laboratories that involve forensic anthropology, The Forensic Anthropology Laboratory reveals the ways in which anthropologists document, process, and collect data for academic research and practical and legal applications, including time of death, trauma analyses, and the identification of unknown human remains. Drawing from a wide range of sources, the book begins with detailed descriptions of how body donations are received and processed. It includes extraordinary photos documenting the steps taken to ensure that each body part is tracked from the moment it is received through the decomposition and skeletonization processes. Dr. David Hunt, of the Smithsonian Institution, discusses destructive analysis, diagnostic imaging, casting, and all types of anthroposcopic and anthropometric data collection methods. The book also compares the duties of full-time forensic anthropologists in a medical examiner's office with their academic counterparts, discussing staffing, physical plant concerns, field recovery procedures, and laboratory processing. It stresses the variety of required skills, including fingerprinting and other trace evidence procedures, and highlights casework examples from FACES, illustrating the technology used to establish identifications through facial reconstruction, photographic superimposition, and age progression. Using examples from the World Trade Center, Hurricane Katrina, and the Asian Tsunami disasters, the book examines the roles of forensic anthropologists and pathologists as mass fatality responders. It discusses practical issues and explains how and where the mobile disaster morgue can be used, including morgue floor plans and equipment. A one-of-a-kind survey of a variety of forensic anthropology laboratories, the editors provide an insider's view of functioning laboratories as reported by some of the most respected and prolific anthropologists in clinical, research, and academic settings.

This volume presents a systems approach to understanding and managing the AIDS crisis - an approach that addresses the needs not only of HIV- infected individuals, but also of families and communities at risk from AIDS. Discussions are included on HIV epidemiology and risk reduction, medical management of the AIDS patient, and neuropsychiatric aspects of HIV infection. Strategies for psychotherapeutic intervention, from individual through group to extended family system, are described in detail. The authors examine spiritual, religious and cultural factors in communities and offer guidelines for building a community network for AIDS prevention and intervention. Full consideration is also given to ethical and policy issues, and to the risks faced by health care providers. First published in 1993. Routledge is an imprint of Taylor & Francis, an informa company.

The COVID-19 pandemic shocked the world. It shouldn't have. Since this century's turn, epidemiologists have warned of new infectious diseases. Indeed, H1N1, H7N9, SARS, MERS, Ebola Makona, Zika, and a variety of lesser viruses have emerged almost annually. But what of the epidemiologists themselves? Some bravely descended into the caves where bat species hosted coronaviruses, including the strains that evolved into the COVID-19 virus. Yet, despite their own warnings, many of the researchers appear unable to understand the true nature of the disease-as if they are dead to what they've seen. Dead Epidemiologists is an eclectic collection of commentaries, articles, and interviews revealing the hidden-in-plain-sight truth behind the pandemic: Global capital drove the deforestation and development that exposed us to new pathogens. Rob Wallace and his colleagues-ecologists, geographers, activists, and, yes, epidemiologists-unpack the material and conceptual origins of COVID-19. From deepest Yunnan to the boardrooms of New York City, this book offers a compelling diagnosis of the roots of COVID-19, and a stark prognosis of what-without further intervention-may come.

This book offers an accessible and up-to-date reference on primate zoonoses. Recent years have witnessed a rise in human diseases zoonotically transferred from animals, with wild primates implicated in the spread of numerous newly emerging infections. The authors go beyond simply providing an inventory of diseases, helping readers to understand how and why they are transmitted. Important consideration is given to the contemporary cultural and ecological factors involved.

This book examines the issue of ethics in the context of the provision of military health care in an epidemic. Outbreaks of epidemics like Ebola trigger difficult ethical challenges for civilian and military health care personnel. This book offers theoretical reflections combined with reports from recent military and NGO missions in the field. The authors of this volume focus on military medical ethics adding a distinct voice to the topic of epidemics and infectious diseases. While military health care personnel are always crucially involved during disaster relief operations and large-scale public health emergencies, most of the current literature treats ethical issues during epidemics from a more general perspective without taking into account the specifics of the military context. The contributions in this volume provide first-hand insights into some of the ethical issues encountered by military health care personnel in missions during the Ebola outbreak in 2014/2015. This practical perspective is complimented by academic analyses and theoretical reflections on ethical issues associated with epidemics. This book will be of much interest to students of military studies, ethics and African politics.

Edited by a clinical psychologist who has been on the ground helping to develop psychosocial support for Ebola survivors in one of the hardest-hit regions of West Africa, this book explains the devastating emotional aspects of the epidemic and its impact on survivors and the population in West Africa, families in the diaspora, and people in the United States and other countries. It also describes lessons learned from past epidemics like HIV/AIDS and SARS, and valuable approaches to healing from future epidemics. While the devastating Ebola epidemic has been contained, the effects of this outbreak—referred to by the World Health Organization as "the most severe acute public health emergency seen in modern times"—have wreaked a tremendous emotional toll on the populations of West Africa as well as on families and survivors worldwide. This groundbreaking book covers the psychosocial needs, programs, and policies related to the Ebola epidemic and examines broader lessons of the outbreak, such as changes in the ways in which healing from future epidemics can be handled. Edited by Judy Kuriansky, PhD, a noted clinical psychologist and United Nations NGO representative with extensive experience helping after disasters worldwide, and direct experience gained from being "on the ground" in West Africa in the midst of the epidemic, this book identifies and explains universal psychological factors at play in all such crises. It debunks myths regarding Ebola and describes the resulting psychological and social harm caused by the epidemic. The chapters cover overarching emotional issues and problems as well as the long-term impact on at-risk groups, such as children, women, and health workers; the impact of emotional issues on social and economic life; responses of government officials, media, and various aid organizations; and solutions being offered by groups worldwide, including service and humanitarian organizations, politicians, policymakers, and public health education groups.

Extracted from the Drug Abuse Handbook, 2nd edition, to give you just the information you need at an affordable price.

Postmortem Toxicology of Abused Drugs considers the role of toxicology in the investigation of homicide, suicide, accident, natural death, and overdose. It gives practical insights and case reviews on conducting toxicology tests and completing toxicology reports. It explains chain of custody; specimen collection and security; sampling of blood, urine, bile, and vitreous humor; and the selection of post-mortem specimens. Analyzing various testing procedures, the book covers simple chemical tests, microdiffusion tests, chromatography, spectroscopy, and more. It also discusses methods and strategies for analysis; and covers quality assurance protocols and controls. To help avoid common pitfalls, the text demonstrates the proper interpretation of postmortem drug levels based on knowledge of pharmacokinetics, metabolism, and pharmacogenetics; post-mortem redistribution and diffusion; and other considerations such as synergistic toxicity, and drug instability. Heavily referenced and containing several tables, figures, and useful appendices, this book is a handy reference for forensic scientists and medical examiners involved with death investigation.

Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals with time-to-event data that is complicated by censoring and the dynamic nature of events occurring in time. With chapters written by leading researchers in the field, the handbook focuses on advances in survival analysis techniques, covering classical and Bayesian approaches. It gives a complete overview of the current status of survival analysis and should inspire further research in the field. Accessible to a wide range of readers, the book provides: An introduction to various areas in survival analysis for graduate students and novices A reference to modern investigations into survival analysis for more established researchers A text or supplement for a second or advanced course in survival analysis A useful guide to statistical methods for analyzing survival data experiments for practicing statisticians

Handbook of Statistical Methods for Case-Control Studies is written by leading researchers in the field. It provides an in-depth treatment of up-to-date and currently developing statistical methods for the design and analysis of case-control studies, as well as a review of classical principles and methods. The handbook is designed to serve as a reference text for biostatisticians and quantitatively-oriented epidemiologists who are working on the design and analysis of case-control studies or on related statistical methods research. Though not specifically intended as a textbook, it may also be used as a backup reference text for graduate level courses. Book Sections Classical designs and causal inference, measurement error, power, and small-sample inference Designs that use full-cohort information Time-to-event data Genetic epidemiology About the Editors Ornulf Borgan is Professor of Statistics, University of Oslo. His book with Andersen, Gill and Keiding on counting processes in survival analysis is a world classic. Norman E. Breslow was, at the time of his death, Professor Emeritus in Biostatistics, University of Washington. For decades, his book with Nick Day has been the authoritative text on case-control methodology. Nilanjan Chatterjee is Bloomberg Distinguished Professor, Johns Hopkins University. He leads a broad research program in statistical methods for modern large scale biomedical studies. Mitchell H. Gail is a Senior Investigator at the National Cancer Institute. His research includes modeling absolute risk of disease, intervention trials, and statistical methods for epidemiology. Alastair Scott was, at the time of his death, Professor Emeritus of Statistics, University of Auckland. He was a major contributor to using survey sampling methods for analyzing case-control data. Chris J. Wild is Professor of Statistics, University of Auckland. His research includes nonlinear regression and methods for fitting models to response-selective data.