Best Quality of Life & Pharmacoeconomics: An Introduction

Quality of Life & Pharmacoeconomics: An Introduction by Lippincott Williams & Wilkins




Quality of Life & Pharmacoeconomics: An Introduction will familiarize students, clinicians, and researchers with the key principles and methods of quality-of-life and cost-effectiveness assessment in clinical trials. The book is based on abstracted material from the Second Edition of Dr. Spilker's definitive reference, Quality of Life and Pharmacoeconomics in Clinical Trials (1996). The material has been edited, condensed, and streamlined to provide a broad overview of approaches to quality-of-life assessment, evaluations of outcomes, and pharmacoeconomic methods. The integration of these three areas is one of the most valuable features of this introduction. Quality of Life & Pharmacoeconomics: An Introduction is divided into seven sections: introduction; social and psychological assessment; selected tests for quality-of-life assessment; reported methodology; special populations and specific diseases; utilities and outcomes; and pharmacoeconomics. Each section summarizes the crucial issues and provides selected referencesRead more Quality of Life & Pharmacoeconomics: An Introduction

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This book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. Meta-analysis has become a critically important tool in fields as diverse as medicine, pharmacology, epidemiology, education, psychology, business, and ecology. Introduction to Meta-Analysis:

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A superb combination of lucid prose and informative graphics, written by four of the world’s leading experts on all aspects of meta-analysis. Borenstein, Hedges, Higgins, and Rothstein provide a refreshing departure from cookbook approaches with their clear explanations of the what and why of meta-analysis. The book is ideal as a course textbook or for self-study. My students, who used pre-publication versions of some of the chapters, raved about the clarity of the explanations and examples. David Rindskopf, Distinguished Professor of Educational Psychology, City University of New York, Graduate School and University Center, & Editor of the Journal of Educational and Behavioral Statistics.

The approach taken by Introduction to Meta-analysis is intended to be primarily conceptual, and it is amazingly successful at achieving that goal. The reader can comfortably skip the formulas and still understand their application and underlying motivation. For the more statistically sophisticated reader, the relevant formulas and worked examples provide a superb practical guide to performing a meta-analysis. The book provides an eclectic mix of examples from education, social science, biomedical studies, and even ecology. For anyone considering leading a course in meta-analysis, or pursuing self-directed study, Introduction to Meta-analysis would be a clear first choice. Jesse A. Berlin, ScD 

Introduction to Meta-Analysis is an excellent resource for novices and experts alike. The book provides a clear and comprehensive presentation of all basic and most advanced approaches to meta-analysis. This book will be referenced for decades. Michael A. McDaniel, Professor of Human Resources and Organizational Behavior, Virginia Commonwealth University

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This illustrated textbook for biologists provides a refreshingly clear and authoritative introduction to the key ideas of sampling, experimental design, and statistical analysis. The author presents statistical concepts through common sense, non-mathematical explanations and diagrams. These are followed by the relevant formulae and illustrated by worked examples. The examples are drawn from all areas of biology, from biochemistry to ecology and from cell to animal biology. The book provides everything required in an introductory statistics course for biology undergraduates, and it is also useful for more specialized undergraduate courses in ecology, botany, and zoology.

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An Introduction to Medical Statistics (Oxford Medical Publications) by Oxford University Press, USA




Now in its Third Edition, An Introduction to Medical Statistics continues to be and invaluable textbook for medical students, doctors, medical researchers, nurses, members of professionals allied to medicine as well as those concerned with medical data. The material covered includes all the statistical work that would be required for a course in medicine and for the examinations of most of the Royal Colleges. It includes the design of clinical trials and epidemiological studies, data collection, summarizing and presenting data, probability, standard error, confidence intervals and significance tests, techniques of data analysis including multifactorial methods and the choice of statistical method, problems of medical measurement and diagnosis, vital statistics, and calculation of sample size. The new edition describes the design and analysis of medical research studies in a clear and user friendly manner. The third edition includes new topics such as consent in clinical trials, design and analysis of cluster-randomized trials, ecological studies, conditional probability, repeated testing, random effects models, intraclass correlation and conditional odds ratios. Material which is encountered only at the postgraduate level has been indicated clearly in the text to facilitate ease or use. The book is firmly grounded in medical data, particularly in medical research, and includes real illustrative examples. There are 100 multiple choice questions and 17 long questions involving calculations to which fully explained solutions are provided. A new companion volume, Statisitical questions in evidence based medicine (Bland & Peacock, 2000) refers directly to this new edition. This new book of questions and answers includes no calculations and is complementary to the exercises given here.Read more An Introduction to Medical Statistics (Oxford Medical Publications)

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This accessible introduction to data analysis focuses on the interpretation of statistical results, in particular those which come from nonexperimental social research. It will provide social science researchers with the tools necessary to select and evaluate statistical tests appropriate for their research question.

Using a consistent data-set throughout the book to illustrate the various analytic techniques, Michael Lewis-Beck covers topics such as univariate statistics, measures of association, the statistical significance of the relationship between two variables, simple regression in which the dependent variable is influenced by a single independent variable, and multiple regression.

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Bridge the gap between research and practice with DePoy and Gitlin's Introduction to Research: Understanding and Applying Multiple Strategies, 4th Edition. This completely updated, user-friendly text helps you better understand not only the research process, but also research designs and their applications to the real world of clinical practice. Covering multiple research strategies (including both qualitative and quantitative research), it gives you a balanced approach to various research traditions, addressing emerging key issues in today's health care environment.

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The increasing cost of research means that scientists are in more urgent need of optimal design theory to increase the efficiency of parameter estimators and the statistical power of their tests.

The objectives of a good design are to provide interpretable and accurate inference at minimal costs. Optimal design theory can help to identify a design with maximum power and maximum information for a statistical model and, at the same time, enable researchers to check on the model assumptions.

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Researchers and students studying social, behavioural and biomedical sciences will find this book useful for understanding design issues and in putting optimal design ideas to practice. 

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Arranged to facilitate use and highlight key concepts, this clear and concise text also includes many practical exercises, case studies, and real-world applications. Utilizing the modern biostatistical approach to studying disease, Epidemiology Kept Simple, Second Edition will provide readers with the tools to interpret epidemiological data, understand disease concepts, and prepare for board exams. The author fully explains all new terminology and minimizes the use of technical language, while emphasizing real-life practice in modern public health and biomedical research settings.

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In the past thirty years epidemiology has matured from a fledgling scientific field into a vibrant discipline that brings together the biological and social sciences, and in doing so draws upon disciplines ranging from statistics and survey sampling to the philosophy of science. These areas of knowledge have converged into a modern theory of epidemiology that has been slow to penetrate into textbooks, particularly at the introductory level. Epidemiology: An Introduction closes the gap. It begins with a brief, lucid discussion of causal thinking and causal inference and then takes the reader through the elements of epidemiology, focusing on the measures of disease occurrence and causal effects. With these building blocks in place, the reader learns how to design, analyze and interpret problems that epidemiologists face, including confounding, the role of chance, and the exploration of interactions. All these topics are layered on the foundation of basic principles presented in simple language, with numerous examples and questions for further thought.

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This textbook offers an accessible and comprehensive introduction to statistics for all undergraduate psychology students, but particularly those in their second and third years who have already covered an initial introductory course. It covers all of the key areas in quantitative methods including sampling, significance tests, regression, and multivariate techniques and incorporates a range of exercises and problems at the end of each chapter for the student to follow.

The free CD-ROM with tutorial modules complements and enhances the exercises in the text, offers scope for distance learning, and makes both the traditional and non-traditional approaches much more accessible.

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A companion website is available for this text! Click here.

Statistics for Health Care Professionals is an accessible guide to understanding statistics within health care practice. Focusing on quantitative approaches to investigating problems, the book introduces the basic rules and principles of statistics.

Challenging the notion that statistics are often incomprehensible and complex to use, the authors begin by presenting a `how to' section explaining how specific statistical tests can be performed. They also help readers to understand the language of statistics, which is often a stumbling block for those coming to the subject for the first time. The reader is taught how to calculate statistics by hand as well as being introduced to computer packages to make life easier, and then how to analyse these results.

As the results of health care research are so integral to decision-making and developing new practice within the profession, the book encourages the reader to think critically about data analysis and research design, and how these can impact upon evidence based practice. This critical stance is also crucial in the assessment of the many reports and documents issued within the health industry.

Statistics for Health Care Professionals includes practical examples of statistical techniques throughout, and the exercises within and at the end of each chapter help readers to learn and to develop proficiency. There is also a glossary at the end of the book for quick and easy referencing.

This book is essential reading for those coming to statistics for the first time within a health care setting.

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Epidemiology concerns the frequency, pattern, and causes of disease in populations. It is one of the most important modern sciences underpinning health and healthcare- including medicine, public health and profession allied to medicine. Concepts in Epidemiology explains and illustrates the key concepts(language, principles and methods) that underpin the science of epidemiology and its applications to policy making, health service planning and health promotion. Richly illustrated, there are exercises to help readers deepen their understanding, with detrailed material captured in tables. Each chapter ends in a summary, and all technical and specialized terminology is explained and defined in a glossary. The book places heavy emphasis on integrating the ideas of epidemiology.
Topics include: the nature and scope of epidemiology; the epidemiological concepts of population; variation in disease by time, place and person: error, bias, risk modification and confounding; cause and effect: the concepts of natural history, spectrum, iceberg, population patterns and screening; risk and measures of disease frequency; presentation and interpretation of epidemiological data on risk; study design; and theoretical, ethical, contextual, practical and critical foundations of epidemiology.

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This long awaited second edition of this bestseller continues to provide a comprehensive, user friendly, down-to-earth guide to elementary statistics. The book presents a detailed account of the most important procedures for the analysis of data, from the calculation of simple proportions, to a variety of statistical tests, and the use of regression models for modeling of clinical outcomes.

The level of mathematics is kept to a minimum to make the material easily accessible to the novice, and a multitude of illustrative cases are included in every chapter, drawn from the current research literature. The new edition has been completely revised and updated and includes new chapters on basic quantitative methods, measuring survival, measurement scales, diagnostic testing, bayesian methods, meta-analysis and systematic reviews.

"... After years of trying and failing, this is the only book on statistics that i have managed to read and understand" - Naveed Kirmani, Surgical Registrar, South London Healthcare HHS Trust, UK