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Laboratory Animal Pocket Reference Series: The Laboratory Xenopus sp. by CRC Press

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The extensively revised edition of the best-selling Focus Groups as Qualitative Research continues to provide an excellent guide for researchers across the disciplines.

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With meta-analysis methods playing a crucial role in health research in recent years, this important and clearly-written book provides a much-needed survey of the field.
Meta-analysis provides a framework for combining the results of several clinical trials and drawing inferences about the effectiveness of medical treatments. The move towards evidence-based health care and practice is underpinned by the use of meta-analysis. This book:
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The Agile Approach to Adaptive Research: Optimizing Efficiency in Clinical Development (Wiley Series on Technologies for the Pharmaceutical Industry) Best Reviews

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Apply adaptive research to improve results in drug development

The pharmaceutical industry today faces a deepening crisis: inefficiency in its core business, the development of new drugs. The Agile Approach to Adaptive Research offers a solution. It outlines how adaptive research, using already-available tools and techniques, can enable the industry to streamline clinical trials and reach decision points faster and more efficiently.

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". . . an excellent textbook . . . an indispensable reference for biostatisticians and epidemiologists."
—International Statistical Institute

A new edition of the definitive guide to classical and modern methods of biostatistics

Biostatistics consists of various quantitative techniques that are essential to the description and evaluation of relationships among biologic and medical phenomena. Biostatistical Methods: The Assessment of Relative Risks, Second Edition develops basic concepts and derives an expanded array of biostatistical methods through the application of both classical statistical tools and more modern likelihood-based theories. With its fluid and balanced presentation, the book guides readers through the important statistical methods for the assessment of absolute and relative risks in epidemiologic studies and clinical trials with categorical, count, and event-time data.

Presenting a broad scope of coverage and the latest research on the topic, the author begins with categorical data analysis methods for cross-sectional, prospective, and retrospective studies of binary, polychotomous, and ordinal data. Subsequent chapters present modern model-based approaches that include unconditional and conditional logistic regression; Poisson and negative binomial models for count data; and the analysis of event-time data including the Cox proportional hazards model and its generalizations. The book now includes an introduction to mixed models with fixed and random effects as well as expanded methods for evaluation of sample size and power. Additional new topics featured in this Second Edition include:

• Establishing equivalence and non-inferiority
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• Negative binomial models for count data as an alternative to the Poisson model
• GEE models for the analysis of longitudinal repeated measures and multivariate observations

Throughout the book, SAS is utilized to illustrate applications to numerous real-world examples and case studies. A related website features all the data used in examples and problem sets along with the author's SAS routines.

Biostatistical Methods, Second Edition is an excellent book for biostatistics courses at the graduate level. It is also an invaluable reference for biostatisticians, applied statisticians, and epidemiologists.

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In today's rapidly changing world of clinical practice, old assumptions quickly fall under the weight of new evidence. But to make effective clinical decisions, you must face a deluge of data published in the health research literature.

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• StudyingaStudy.com Website is an integral feature of this edition providing interactive materials for all sections of the book. The Website provides practice using the M.A.A.R.I.E. framework, interactive flaw-catching and Selecting a Statistics exercises, self-testing questions-answers and exercises using abstracts from real articles.
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PDQ Statistics, Third Edition offers an expert overview of all major statistical methods, giving the reader a thorough understanding of statistics and how they are used in research articles. The book covers the major categories variable and descriptive statistics, parametric statistics, non-parametric statistics, and multivariate statistics. The explanations are clear, succinct, and loaded with practical examples. This third edition includes new chapters on hierarchical and logistic regression, path analysis, and structural equation modeling. PDQ Statistics, Third Edition also helps the reader identify those statistical analyses with basic flaws in design or research. The book s attractive design and humorous writing style make the subject matter accessible and engaging.

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The forty-year "Tuskegee" Syphilis Study has become the American metaphor for medical racism, government malfeasance, and physician arrogance. The subject of histories, films, rumors, and political slogans, it received an official federal apology from President Bill Clinton in a White House ceremony.

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This work provides descriptions, explanations and examples of the Bayesian approach to statistics, demonstrating the utility of Bayesian methods for analyzing real-world problems in the health sciences. The work considers the individual components of Bayesian analysis.;College or university bookstores may order five or more copies at a special student price, available on request from Marcel Dekker, Inc.

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Main Features : Design and Analysis of Clinical Trials: Concept and Methodologies (Wiley Series in Probability and Statistics)

A unique, unifying treatment for statistics and science in clinical trials

What sets this volume apart from the many books dealing with clinical trials is its integration of statistical and clinical disciplines. Stressing communication between biostatisticians and clinical scientists, this work clearly relates statistical interpretation to clinical issues arising in different stages of pharmaceutical research and development. Plus, the principles presented here are universal enough to be easily adapted in non-biopharmaceutical settings.

Design and Analysis of Clinical Trials tackles concepts and methodologies. It not only covers statistical basics such as uncertainty and bias, design considerations such as patient selection, randomization, and the different types of clinical trials but also deals with various methods of data analysis, group sequential procedures for interim analysis, efficacy data evaluation, analysis of safety data, and more. Throughout, the book:
* Surveys current and emerging clinical issues and newly developed statistical methods
* Presents a critical review of statistical methodologies in various therapeutic areas
* Features case studies from actual clinical trials
* Minimizes the mathematics involved, making the material widely accessible
* Offers each chapter as a self-contained entity
* Includes illustrations to highlight the text

This monumental reference on all facets of clinical trials is important reading for physicians, clinical and medical researchers, pharmaceutical scientists, clinical programmers, biostatisticians, and anyone involved in this burgeoning area of clinical research. It can also be used as a textbook in graduate-level courses in the field.

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Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence (Wiley Series in Probability and Statistics)

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"Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence (Wiley Series in Probability and Statistics)" Feature

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.