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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. Comprising an up-to-date overview of the statistical analysis of cost-effectiveness data, the book is supported by numerous worked examples from the author’s own experience. It has been written in a style suitable for medical statisticians and health care professionals alike. Key features include: an overview of statistical methods used in the analysis of cost-effectiveness data. coverage of Bayesian methodology. illustrated throughout by worked examples using real data. suitability for health care professionals with limited statistical knowledge. discussion of software used for data analysis. An essential reference for biostatisticians and health economists engaged in cost-effectiveness analysis of health-care interventions, both in academia and industry. Also of interest to graduate students of biostatistics, public health and economics.
Cancer is a major healthcare burden across the world and impacts not only the people diagnosed with various cancers but also their families, carers, and healthcare systems. With advances in the diagnosis and treatment, more people are diagnosed early and receive treatments for a disease where few treatments options were previously available. As a result, the survival of patients with cancer has steadily improved and, in most cases, patients who are not cured may receive multiple lines of treatment, often with financial consequences for the patients, insurers and healthcare systems. Although many books exist that address economic evaluation, Economic Evaluation of Cancer Drugs using Clinical Trial and Real World Data is the first unified text that specifically addresses the economic evaluation of cancer drugs. The authors discuss how to perform cost-effectiveness analyses while emphasising the strategic importance of designing cost-effectiveness into cancer trials and building robust economic evaluation models that have a higher chance of reimbursement if truly cost-effective. They cover the use of real-world data using cancer registries and discuss how such data can support or complement clinical trials with limited follow up. Lessons learned from failed reimbursement attempts, factors predictive of successful reimbursement and the different payer requirements across major countries including US, Australia, Canada, UK, Germany, France and Italy are also discussed. The book includes many detailed practical examples, case studies and thought-provoking exercises for use in classroom and seminar discussions. Iftekhar Khan is a medical statistician and health economist and a lead statistician at Oxford Unviersity’s Center for Statistics in Medicine. Professor Khan is also a Senior Research Fellow in Health Economics at University of Warwick and is a Senior Statistical Assessor within the Licensing Division of the UK Medicine and Health Regulation Agency. Ralph Crott is a former professor in Pharmacoeconomics at the University of Montreal in Quebec, Canada and former head of the EORTC Health Economics Unit and former senior health economist at the Belgian HTA organization. Zahid Bashir has over twelve years experience working in the pharmaceutical industry in medical affairs and oncology drug development where he is involved in the design and execution of oncology clinical trials and development of reimbursement dossiers for HTA submission.
It is becoming increasingly important to examine the relationship between the outcomes of a clinical trial and the costs of the medical therapy under study. The results of such analysis can affect reimbursement decisions for new medical technologies, drugs, devices or diagnostics. It can aid companies seeking to make claims about the cost-effectiveness of their product, as well as allowing early consideration of the economic value of therapies which may be important to improving initial adoption decisions. It is also vital for addressing the requirements of regulatory bodies. Economic Evaluation in Clinical Trials provides practical advice on how to conduct cost-effectiveness analyses in controlled trials of medical therapies. This new edition has been extensively rewritten and revised; topics discussed range from design issues such as the types of services that should be measured and price weights, to assessment of quality-adjusted life years. Illustrative materials, case histories and worked examples are included to encourage the reader to apply the methods discussed. These exercises are supported with datasets, programmes and solutions made available online.
This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data. This book is part of the SAS Press program.
A unique, in-depth discussion of the uses and conduct of cost-effectiveness analyses (CEAs) as decision-making aids in the health and medical fields, this volume is the product of over two years of comprehensive research and deliberation by a multi-disciplinary panel of economists, ethicists, psychometricians, and clinicians. Exploring cost-effectiveness in the context of societal decision-making for resource allocation purposes, this volume proposes that analysts include a "reference-case" analysis in all CEAs designed to inform resource allocation and puts forth the most explicit set of guidelines (together with their rationale) ever defined on the conduct of CEAs. Important theoretical and practical issues encountered in measuring costs and effectiveness, evaluating outcomes, discounting, and dealing with uncertainty are examined in separate chapters. Additional chapters on framing and reporting of CEAs elucidate the purpose of the analysis and the effective communication of its findings. Cost-Effectiveness in Health and Medicine differs from the available literature in several key aspects. Most importantly, it represents a consensus on standard methods--a feature integral to a CEA, whose principal goal is to permit comparisons of the costs and health outcomes of alternative ways of improving health. The detailed level at which the discussion is offered is another major distinction of this book, since guidelines in journal literature and in CEA-related books tend to be rather general--to the extent that the analyst is left with little guidance on specific matters. The focused overview of the theoretical background underlying areas of controversy and of methodological alternatives, and, finally, the accessible writing style make this volume a top choice on the reading lists of analysts in medicine and public health who wish to improve practice and comparability of CEAs. The book will also appeal to decision-makers in government, managed care, and industry who wish to consider the uses and limitations of CEAs.
Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources.The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies.The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences.
This book is intended for the practicing surgeon. It is designed to offer practical insights into the essentials of an epidemiological, statistical and outcomes-based approach to surgical practice. Surgeons are invited to begin to develop the requisite skills that will allow them to communicate effectively with their colleagues in epidemiology and
The Asian Development Bank (ADB) has been continuously undertaking measures to enhance the effectiveness of its operations. To improve projects both at the preparation and implementation stages, ADB issued the Guidelines for Economic Analysis of Projects in 1997 as a means to enhancing project quality at entry. The conduct of proper economic analysis helps ensure the efficient use of development funds and public resources and thereby increase aid effectiveness. This practical guide is a supplement to the Guidelines for the Economic Analysis of Projects. It provides an overview of recent methodological developments in cost-benefit analysis as well as suggested improvements in the economic analysis of projects in selected sectors through case studies. These case studies illustrate the application of suggested methodologies, taking into account sector-specific needs, as well as difficulties faced by practitioners in terms of data and time constraints during project processing. It also aims to contribute to ADB’s capacity building initiatives as this will be the main reference material for conduct of economic analysis.
This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.