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Written at a level suitable for graduate students working in medical statistics, this collection highlights four areas of active research: survival analysis, longitudinal data analysis, Bayesian methods, and imaging. Each article has been commissioned from leaders in the fields, and the collection reflects the rapid growth and wide application of statistical methods in medicine. Equally valuable for students and researchers, the book provides a practical introduction to current methods.

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Best Statistical Methods in Cancer Research Vol. 1 : The Analysis of Case-Control Studies

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****** Save Statistics for Technology: A Course in Applied Statistics, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)

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Statistics for Technology: A Course in Applied Statistics, Third Edition (Chapman & Hall/CRC Texts in Statistical Science) Description

One of the most popular introductory texts in its field, Statistics for Technology: A Course in Applied Studies presents the range of statistical methods commonly used in science, social science, and engineering.
The mathematics are simple and straightforward; statistical concepts are explained carefully; and real-life (rather than contrived) examples are used throughout the chapters.
Divided into three parts, the Introduction describes some simple methods of summarizing data. Theory examines the basic concepts and theory of statistics. Applications covers the planning and procedures of experiments, quality control, and life testing.
Revised throughout, this Third Edition places a higher priority on the role of computers in analysis, and many new references have been incorporated. A new appendix describes general methods of tackling statistical problems, including guidance on literature searching and report writing.

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Most medical researchers, whether clinical or non-clinical, receive some background in statistics as undergraduates. However, it is most often brief, a long time ago, and largely forgotten by the time it is needed. Furthermore, many introductory texts fall short of adequately explaining the underlying concepts of statistics, and often are divorced from the reality of conducting and assessing medical research.

Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background.

The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. The text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.

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Statistics in Practice A new series of practical books outlining the use of statistical techniques in a wide range of application areas:
* Human and Biological Sciences
* Earth and Environmental Sciences
* Industry, Commerce and Finance
Statistical Issues in Drug Development Stephen Senn Professor of Pharmaceutical & Health Statistics, University College, London Statistical Issues in Drug Development provides an accessible text for those working directly in drug development, regulatory and marketing departments within the pharmaceutical industry. As a consequence of regulatory authorities demanding increasingly higher standards, statistics has become a critical element in the design and conduct of drug development programmes. The concepts covered in this volume guide the non-statistician through the most pressing statistical issues and controversies in drug development. Key issues covered include:
* Design & interpretation of clinical trials
* Bayesian & frequentist methods
* Sequential & cross-over trials
* Drug monitoring & pharmaco-economics
The book has been prepared in two sections. The first section considers the role of statistics in drug development from four different perspectives: historical, philosophical, technical and professional. The second section covers a series of controversial topics such as fixed versus random effects for meta-analysis, one-sided versus two-sided tests and the ethics of placebo run-ins. The approachable and wide-ranging coverage of this book will make it invaluable to all those working in drug development and regulation.

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****** Statistical Questions in Evidence-Based Medicine

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Statistical Questions in Evidence-Based Medicine Description

Statistical Questions in Evidence-based Medicine is a book of questions and answers about the statistical principles and methods used in medical research. Based entirely on material published in the medical literature and popular media, it will prove invaluable to medical students, doctors, nurses, medical researchers and others concerned with medical data. This book is a companion volume to the new 3rd edition of An Introduction to Medical Statistics but can also be used in conjunction with the 2nd edition or with other good texts. Short excerpts of material from published papers or summaries of their results are presented with questions. These test and develop the reader's understanding and interpretation of statistics and extend the reader's research and critical appraisal skills, thus encouraging an evidence-based approach. Questions are presented on the left-hand page with detailed answers on the right-hand page. Answers include references to core material in An Introduction to Medical Statistics. The book is intended as a series of examples for self-teaching but could also be read as a series of case studies with detailed commentaries. The questions are clearly graded, using icons, in terms of difficulty and undergraduate or postgraduate level. The book is easy to use and a model of clarity for the reader.

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Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence acts as a source of basic methods for scientists wanting to combine evidence from different experiments. The authors aim to promote a deeper understanding of the notion of statistical evidence.

The book is comprised of two parts – The Handbook, and The Theory. The Handbook is a guide for combining and interpreting experimental evidence to solve standard statistical problems. This section allows someone with a rudimentary knowledge in general statistics to apply the methods. The Theory provides the motivation, theory and results of simulation experiments to justify the methodology.

This is a coherent introduction to the statistical concepts required to understand the authors’ thesis that evidence in a test statistic can often be calibrated when transformed to the right scale.

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Hirsch and Riegelman have recognized the need for a text to explain, to a wide audience, statistical concepts rather than mathematics or terminology. They therefore expand on traditional mathematical methods by using graohics illustrating mathematical ideas, working through scores of examples from medical cases and literature, and employing non-technical terminology. Thus, they aim to provide the reader with an understanding of the terminology and mathematics without the rote learning that traditional methods require. The book presents the basic principles of statistics common to all methods of analysis and covers the logical processes used by statisticians to select statistical procedures for a particular set of data. Included is free software (STAT-PLUS) from the authors, and a free teacher's guide contains problems and answers, worked examples, flow charts and statistical tables.

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This engaging new book provides comprehensive coverage of research methods as well as a foundation in statistical analysis vital for individuals in the communication sciences and disorders field. While most speech-language pathologists and audiologists pursue clinical practice rather than research careers, it is important to understand the scientific base that their clinical work is built upon. Successful evidence-based clinical practice is rooted in this understanding. Research and Statistical Methods in Communication Sciences and Disorders covers the principles of research design, data analysis, and presentation of findings necessary for individuals performing research as well as consumers of scientific literature. Filled with meaningful examples, written in readable language, and pertinent to both speech-language pathology and audiology, this resource provides the essential knowledge of scientific reasoning and methods for scientific inquiry necessary to perform and understand research.

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All in all, we are actually suggest Epidemiology: Study Design and Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) fou you. This on-line sellers supply the best quality and save price value which integrated super conserve shipping (in U.S.A. only). Reading opinions offers you with a a whole lot of fuller details in the cons and pros on the Epidemiology: Study Design and Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science).

Building an up-to-date understanding of the methodologies that can be used to shape public health policies, Epidemiology: Study Design and Data Analysis, Second Edition encompasses the study of epidemiology from the observation of associations between risk factors and disease to the use of practical, data-supported analyses. It presents study designs commonly used for a wide range of purposes, and covers the spectrum of statistical principles and analytical tools used in epidemiological research, such as techniques used in report writing, descriptive analyses, statistical models and synthesis of evidence.

New Material in This Edition Includes:

Systematic evaluation

Meta-analysis

Regression dilution

Case-cohort studies

Case-crossover studies

Pooled logistic regression

Companion Web site containing data sets for examples and exercises, SAS and Stata code for examples, a sample size calculator, and a SAS floating absolute risk macro

The second edition of a popular textbook, this book emphasizes quantitative and design aspects of epidemiological research. The author favors the use of basic mathematics and practical methods over complicated mathematical proofs, making this an ideal textbook that is comprehensive yet accessible to graduate students in epidemiology, statistics, public health studies, and/or medical research.

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+++ Statistical Monitoring of Clinical Trials: A Unified Approach (Statistics for Biology and Health) reviews

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The approach taken in this book is, to studies monitored over time, what the Central Limit Theorem is to studies with only one analysis. Just as the Central Limit Theorem shows that test statistics involving very different types of clinical trial outcomes are asymptotically normal, this book shows that the joint distribution of the test statistics at different analysis times is asymptotically multivariate normal with the correlation structure of Brownian motion ("the B-value") – irrespective of the test statistic. Thus, this book offers statisticians an accessible, incremental approach to understanding Brownian motion as related to clinical trials.

****** Save Introduction to Randomized Controlled Clinical Trials, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

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Introduction to Randomized Controlled Clinical Trials, Second Edition (Chapman & Hall/CRC Texts in Statistical Science) Description

Evidence from randomized controlled clinical trials is widely accepted as the only sound basis for assessing the efficacy of new medical treatments. Statistical methods play a key role in all stages of these trials, including their justification, design, and analysis. This second edition of Introduction to Randomized Controlled Clinical Trials provides a concise presentation of the principles applied in this area. It details the concepts behind randomization and methods for designing and analyzing trials and also includes information on meta-analysis and specialized designs, such as cross-over trials, cluster-randomized designs, and equivalence studies.

This latest edition features new and revised references, examples, exercises, and a new chapter dedicated to binary outcomes and survival analysis. It also presents numerous examples taken from the medical literature, contains exercises at the end of each chapter, and offers solutions in an appendix. The author uses Minitab and R software throughout the text for implementing the methods that are presented.

Comprehensive and accessible, Introduction to Randomized Controlled Clinical Trials is well-suited for those familiar with elementary statistical ideas and methods who want to further their knowledge of the subject.

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The explanation and implementation of statistical methods for the medical researcher or statistician remains an integral part of modern medical research. This book explains the use of experimental and analytical biostatistics systems. Its accessible style allows it to be used by the non-mathematician as a fundamental component of successful research.

Since the third edition, there have been many developments in statistical techniques. The fourth edition provides the medical statistician with an accessible guide to these techniques and to reflect the extent of their usage in medical research.

The new edition takes a much more comprehensive approach to its subject. There has been a radical reorganization of the text to improve the continuity and cohesion of the presentation and to extend the scope by covering many new ideas now being introduced into the analysis of medical research data. The authors have tried to maintain the modest level of mathematical exposition that characterized the earlier editions, essentially confining the mathematics to the statement of algebraic formulae rather than pursuing mathematical proofs.

Received the Highly Commended Certificate in the Public Health Category of the 2002 BMA Books Competition.

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The new edition adds a chapter on multiple linear regression in biomedical research, with sections including the multiple linear regressions model and least squares; the ANOVA table, parameter estimates, and confidence intervals; partial f-tests; polynomial regression; and analysis of covariance.
* Organized by problem rather than method, so it guides readers to the correct technique for solving the problem at hand.

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Statistical Evidence in Medical Trials is a lucid, well-written and entertaining text that addresses common pitfalls in evaluating medical research. Including extensive use of publications from the medical literature and a non-technical account of how to appraise the quality of evidence presented in these publications, this book is ideal for health care professionals, students in medical or nursing schools, researchers and students in statistics, and anyone needing to assess the evidence published in medical journals.

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This well-organized and clearly written text has a unique focus on methods of identifying the joint effects of genes and environment on disease patterns. It follows the natural sequence of research, taking readers through the study designs and statistical analysis techniques for determining whether a trait runs in families, testing hypotheses about whether a familial tendency is due to genetic or environmental factors or both, estimating the parameters of a genetic model, localizing and ultimately isolating the responsible genes, and finally characterizing their effects in the population. Examples from the literature on the genetic epidemiology of breast and colorectal cancer, among other diseases, illustrate this process. Although the book is oriented primarily towards graduate students in epidemiology, biostatistics and human genetics, it will also serve as a comprehensive reference work for researchers. Introductory chapters on molecular biology, Mendelian genetics, epidemiology, statistics, and population genetics will help make the book accessible to those coming from one of these fields without a background in the others. It strikes a good balance between epidemiologic study designs and statistical methods of data analysis.

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