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Introduction to Randomized Controlled Clinical Trials Second Edition

Introduction to Randomized Controlled Clinical Trials  Second Edition Author John N.S. Matthews
ISBN-10 9781420011302
Release 2006-06-26
Pages 302
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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.

Introduction to Statistical Methods for Clinical Trials

Introduction to Statistical Methods for Clinical Trials Author Thomas D. Cook
ISBN-10 9781584880271
Release 2007-11-19
Pages 464
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Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors’ collective experiences in this field, Introduction to Statistical Methods for Clinical Trials presents various statistical topics relevant to the design, monitoring, and analysis of a clinical trial. After reviewing the history, ethics, protocol, and regulatory issues of clinical trials, the book provides guidelines for formulating primary and secondary questions and translating clinical questions into statistical ones. It examines designs used in clinical trials, presents methods for determining sample size, and introduces constrained randomization procedures. The authors also discuss how various types of data must be collected to answer key questions in a trial. In addition, they explore common analysis methods, describe statistical methods that determine what an emerging trend represents, and present issues that arise in the analysis of data. The book concludes with suggestions for reporting trial results that are consistent with universal guidelines recommended by medical journals. Developed from a course taught at the University of Wisconsin for the past 25 years, this textbook provides a solid understanding of the statistical approaches used in the design, conduct, and analysis of clinical trials.

Randomized Clinical Trials

Randomized Clinical Trials Author David Machin
ISBN-10 0470319224
Release 2010-05-20
Pages 374
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Using examples and case studies from industry, academia and research literature, Randomized Clinical Trials provides a detailed overview of the key issues involved in designing, conducting, analysing and reporting randomized clinical trials. It examines the methodology for conducting Phase III clinical trials, developing the protocols, the practice for capturing, measuring, and analysing the resulting clinical data and their subsequent reporting. Randomized clinical trials are the principal method for determining the relative efficacy and safety of alternative treatments, interventions or medical devices. They are conducted by groups comprising one or more of pharmaceutical and allied health-care organisations, academic institutions, and charity supported research groups. In many cases such trials provide the key evidence necessary for the regulatory approval of a new product for future patient use. Randomized Clinical Trials provides comprehensive coverage of such trials, ranging from elementary to advanced level. Written by authors with considerable experience of clinical trials, Randomized Clinical Trials is an authoritative guide for clinicians, nurses, data managers and medical statisticians involved in clinical trials research and for health care professionals directly involved in patient care in a clinical trial context.

Clinical Trials

Clinical Trials Author Steven Piantadosi
ISBN-10 9781118959213
Release 2017-10-09
Pages 896
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Presents elements of clinical trial methods that are essential in planning, designing, conducting, analyzing, and interpreting clinical trials with the goal of improving the evidence derived from these important studies This Third Edition builds on the text’s reputation as a straightforward, detailed, and authoritative presentation of quantitative methods for clinical trials. Readers will encounter the principles of design for various types of clinical trials, and are then skillfully guided through the complete process of planning the experiment, assembling a study cohort, assessing data, and reporting results. Throughout the process, the author alerts readers to problems that may arise during the course of the trial and provides common sense solutions. All stages of therapeutic development are discussed in detail, and the methods are not restricted to a single clinical application area. The authors bases current revisions and updates on his own experience, classroom instruction, and feedback from teachers and medical and statistical professionals involved in clinical trials. The Third Edition greatly expands its coverage, ranging from statistical principles to new and provocative topics, including alternative medicine and ethics, middle development, comparative studies, and adaptive designs. At the same time, it offers more pragmatic advice for issues such as selecting outcomes, sample size, analysis, reporting, and handling allegations of misconduct. Readers familiar with the First and Second Editions will discover revamped exercise sets; an updated and extensive reference section; new material on endpoints and the developmental pipeline, among others; and revisions of numerous sections. In addition, this book: • Features accessible and broad coverage of statistical design methods—the crucial building blocks of clinical trials and medical research -- now complete with new chapters on overall development, middle development, comparative studies, and adaptive designs • Teaches readers to design clinical trials that produce valid qualitative results backed by rigorous statistical methods • Contains an introduction and summary in each chapter to reinforce key points • Includes discussion questions to stimulate critical thinking and help readers understand how they can apply their newfound knowledge • Provides extensive references to direct readers to the most recent literature, and there are numerous new or revised exercises throughout the book Clinical Trials: A Methodologic Perspective, Third Edition is a textbook accessible to advanced undergraduate students in the quantitative sciences, graduate students in public health and the life sciences, physicians training in clinical research methods, and biostatisticians and epidemiologists. Steven Piantadosi, MD, PhD, is the Phase One Foundation Distinguished Chair and Director of the Samuel Oschin Cancer Institute, and Professor of Medicine at Cedars-Sinai Medical Center in Los Angeles, California. Dr. Piantadosi is one of the world’s leading experts in the design and analysis of clinical trials for cancer research. He has taught clinical trials methods extensively in formal courses and short venues. He has advised numerous academic programs and collaborations nationally regarding clinical trial design and conduct, and has served on external advisory boards for the National Institutes of Health and other prominent cancer programs and centers. The author of more than 260 peer-reviewed scientific articles, Dr. Piantadosi has published extensively on research results, clinical applications, and trial methodology. While his papers have contributed to many areas of oncology, he has also collaborated on diverse studies outside oncology including lung disease and degenerative neurological disease.

Designing Randomised Trials in Health Education and the Social Sciences

Designing Randomised Trials in Health  Education and the Social Sciences Author D. Torgerson
ISBN-10 9780230583993
Release 2008-03-13
Pages 210
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The book focuses on the design of rigorous trials rather than their statistical underpinnings, with chapters on: pragmatic designs; placebo designs; preference approaches; unequal allocation; economics; analytical approaches; randomization methods. It also includes a detailed description of randomization procedures and different trial designs.

Applied Stochastic Modelling Second Edition

Applied Stochastic Modelling  Second Edition Author Byron J.T. Morgan
ISBN-10 9781420011654
Release 2008-12-02
Pages 368
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Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and statistical theory. Along with an updated bibliography and improved figures, this edition offers numerous updates throughout. New to the Second Edition An extended discussion on Bayesian methods A large number of new exercises A new appendix on computational methods The book covers both contemporary and classical aspects of statistics, including survival analysis, Kernel density estimation, Markov chain Monte Carlo, hypothesis testing, regression, bootstrap, and generalised linear models. Although the book can be used without reference to computational programs, the author provides the option of using powerful computational tools for stochastic modelling. All of the data sets and MATLAB® and R programs found in the text as well as lecture slides and other ancillary material are available for download at Continuing in the bestselling tradition of its predecessor, this textbook remains an excellent resource for teaching students how to fit stochastic models to data.

Cluster Randomised Trials Second Edition

Cluster Randomised Trials  Second Edition Author Richard J. Hayes
ISBN-10 9781315353234
Release 2017-07-06
Pages 398
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Cluster Randomised Trials, Second Edition discusses the design, conduct, and analysis of trials that randomise groups of individuals to different treatments. It explores the advantages of cluster randomisation, with special attention given to evaluating the effects of interventions against infectious diseases. Avoiding unnecessary mathematical detail, the book covers basic concepts underlying the use of cluster randomisation, such as direct, indirect, and total effects. In the time since the publication of the first edition, the use of cluster randomised trials (CRTs) has increased substantially, which is reflected in the updates to this edition. There are greatly expanded sections on randomisation, sample size estimation, and alternative designs, including new material on stepped wedge designs. There is a new section on handling ordinal outcome data, and an appendix with descriptions and/or generating code of the example data sets. Although the book mainly focuses on medical and public health applications, it shows that the rigorous evidence of intervention effects provided by CRTs has the potential to inform public policy in a wide range of other areas. The book encourages readers to apply the methods to their own trials, reproduce the analyses presented, and explore alternative approaches.

Randomization Bootstrap and Monte Carlo Methods in Biology Third Edition

Randomization  Bootstrap and Monte Carlo Methods in Biology  Third Edition Author Bryan F.J. Manly
ISBN-10 1584885416
Release 2006-08-15
Pages 480
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Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. This new edition of the bestselling Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates the value of a number of these methods with an emphasis on biological applications. This textbook focuses on three related areas in computational statistics: randomization, bootstrapping, and Monte Carlo methods of inference. The author emphasizes the sampling approach within randomization testing and confidence intervals. Similar to randomization, the book shows how bootstrapping, or resampling, can be used for confidence intervals and tests of significance. It also explores how to use Monte Carlo methods to test hypotheses and construct confidence intervals. New to the Third Edition Updated information on regression and time series analysis, multivariate methods, survival and growth data as well as software for computational statistics References that reflect recent developments in methodology and computing techniques Additional references on new applications of computer-intensive methods in biology Providing comprehensive coverage of computer-intensive applications while also offering data sets online, Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition supplies a solid foundation for the ever-expanding field of statistics and quantitative analysis in biology.

Introduction to the Theory of Statistical Inference

Introduction to the Theory of Statistical Inference Author Hannelore Liero
ISBN-10 9781466503205
Release 2016-04-19
Pages 284
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Based on the authors’ lecture notes, Introduction to the Theory of Statistical Inference presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Suitable for a second-semester undergraduate course on statistical inference, the book offers proofs to support the mathematics. It illustrates core concepts using cartoons and provides solutions to all examples and problems. Highlights Basic notations and ideas of statistical inference are explained in a mathematically rigorous, but understandable, form Classroom-tested and designed for students of mathematical statistics Examples, applications of the general theory to special cases, exercises, and figures provide a deeper insight into the material Solutions provided for problems formulated at the end of each chapter Combines the theoretical basis of statistical inference with a useful applied toolbox that includes linear models Theoretical, difficult, or frequently misunderstood problems are marked The book is aimed at advanced undergraduate students, graduate students in mathematics and statistics, and theoretically-interested students from other disciplines. Results are presented as theorems and corollaries. All theorems are proven and important statements are formulated as guidelines in prose. With its multipronged and student-tested approach, this book is an excellent introduction to the theory of statistical inference.

Introduction to Statistics in Pharmaceutical Clinical Trials

Introduction to Statistics in Pharmaceutical Clinical Trials Author Todd A. Durham
ISBN-10 0853697140
Release 2008-01-01
Pages 226
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All students of pharmaceutical sciences and clinical research need a solid knowledge and understanding of the nature, methods, application, and importance of statistics. Introduction to Statistics in Pharmaceutical Clinical Trials is an ideal introduction to statistics presented in the context of clinical trials conducted during pharmaceutical drug development. This novel approach both teaches the computational steps needed to conduct analyses and provides a conceptual understanding of how these analyses provide information that forms the rational basis for decision making throughout the drug development process.

Modern Adaptive Randomized Clinical Trials

Modern Adaptive Randomized Clinical Trials Author Oleksandr Sverdlov
ISBN-10 9781482239898
Release 2015-06-30
Pages 533
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Is adaptive randomization always better than traditional fixed-schedule randomization? Which procedures should be used and under which circumstances? What special considerations are required for adaptive randomized trials? What kind of statistical inference should be used to achieve valid and unbiased treatment comparisons following adaptive randomization designs? Modern Adaptive Randomized Clinical Trials: Statistical and Practical Aspects answers these questions and more. From novel designs to cutting-edge applications, this book presents several new and key developments in adaptive randomization. It also offers a fresh and critical look at a number of already-classical topics. Featuring contributions from statisticians, clinical trialists, and subject-matter experts in academia and the pharmaceutical industry, the text: Clarifies the taxonomy of the concept of adaptive randomization Discusses restricted, covariate-adaptive, response-adaptive, and covariate-adjusted response-adaptive (CARA) randomization designs, as well as randomized designs with treatment selection Gives an exposition to many novel adaptive randomization techniques such as brick tunnel randomization, targeted least absolute shrinkage and selection operator (LASSO)-based CARA randomization, multi-arm multi-stage (MAMS) designs, to name a few Addresses the issues of statistical inference following covariate-adaptive and response-adaptive randomization designs Describes a successful implementation of a single pivotal phase II/III adaptive trial in infants with proliferating hemangioma Explores some practical aspects of phase II dose-ranging studies and examines statistical monitoring and interim analysis issues in response-adaptive randomized clinical trials Modern Adaptive Randomized Clinical Trials: Statistical and Practical Aspects covers a wide spectrum of topics related to adaptive randomization designs in contemporary clinical trials. The book provides a thorough exploration of the merits of adaptive randomization and aids in identifying when it is appropriate to apply such designs in practice.

Introduction to General and Generalized Linear Models

Introduction to General and Generalized Linear Models Author Henrik Madsen
ISBN-10 9781439891148
Release 2010-11-09
Pages 316
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Bridging the gap between theory and practice for modern statistical model building, Introduction to General and Generalized Linear Models presents likelihood-based techniques for statistical modelling using various types of data. Implementations using R are provided throughout the text, although other software packages are also discussed. Numerous examples show how the problems are solved with R. After describing the necessary likelihood theory, the book covers both general and generalized linear models using the same likelihood-based methods. It presents the corresponding/parallel results for the general linear models first, since they are easier to understand and often more well known. The authors then explore random effects and mixed effects in a Gaussian context. They also introduce non-Gaussian hierarchical models that are members of the exponential family of distributions. Each chapter contains examples and guidelines for solving the problems via R. Providing a flexible framework for data analysis and model building, this text focuses on the statistical methods and models that can help predict the expected value of an outcome, dependent, or response variable. It offers a sound introduction to general and generalized linear models using the popular and powerful likelihood techniques. Ancillary materials are available at

Sample Size Calculations in Clinical Research Third Edition

Sample Size Calculations in Clinical Research  Third Edition Author Shein-Chung Chow
ISBN-10 9781351727112
Release 2017-08-15
Pages 510
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Praise for the Second Edition: "... this is a useful, comprehensive compendium of almost every possible sample size formula. The strong organization and carefully defined formulae will aid any researcher designing a study." -Biometrics "This impressive book contains formulae for computing sample size in a wide range of settings. One-sample studies and two-sample comparisons for quantitative, binary, and time-to-event outcomes are covered comprehensively, with separate sample size formulae for testing equality, non-inferiority, and equivalence. Many less familiar topics are also covered ..." – Journal of the Royal Statistical Society Sample Size Calculations in Clinical Research, Third Edition presents statistical procedures for performing sample size calculations during various phases of clinical research and development. A comprehensive and unified presentation of statistical concepts and practical applications, this book includes a well-balanced summary of current and emerging clinical issues, regulatory requirements, and recently developed statistical methodologies for sample size calculation. Features: Compares the relative merits and disadvantages of statistical methods for sample size calculations Explains how the formulae and procedures for sample size calculations can be used in a variety of clinical research and development stages Presents real-world examples from several therapeutic areas, including cardiovascular medicine, the central nervous system, anti-infective medicine, oncology, and women’s health Provides sample size calculations for dose response studies, microarray studies, and Bayesian approaches This new edition is updated throughout, includes many new sections, and five new chapters on emerging topics: two stage seamless adaptive designs, cluster randomized trial design, zero-inflated Poisson distribution, clinical trials with extremely low incidence rates, and clinical trial simulation. ?

Randomized Controlled Trials

Randomized Controlled Trials Author Phyllis Solomon
ISBN-10 0199715548
Release 2009-02-02
Pages 224
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Randomized controlled trials (RCTs) are considered by many researchers and providers to be the gold standard of health and social service effectiveness research. However, there exist scant resources that deal with the complex nature of designing and implementing RCTs in community-based settings. This clearly written pocket guide provides researchers and social service practitioners insight into each step of an RCT. The goal of this text is to enable readers to understand, design, and implement a community-based RCT. From the initial stage of planning the RCT and developing its conceptual foundations through implementation, the authors provide a wealth of detail and case studies from social work practice research that assist readers to comprehend the detailed information provided. Accessible, concrete advice is woven throughout the text and tackles the many design and implementation challenges that arise in community practice settings. The importance of utilizing a mix of qualitative and quantitative methods is encouraged due to the intricate nature of RCT research in community-based environments. Through utilizing practical case examples, this pocket guide reviews the essentials of RCTs in a manner that will appeal to researchers, practitioners and students alike who are seeking the necessary tools to build the empirical knowledge base for community-based psychosocial interventions for social work.

Practical Statistics for Medical Research

Practical Statistics for Medical Research Author Douglas G. Altman
ISBN-10 0412276305
Release 1990-11-22
Pages 624
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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.

Applied Categorical and Count Data Analysis

Applied Categorical and Count Data Analysis Author Wan Tang
ISBN-10 9781439806241
Release 2012-06-04
Pages 384
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Developed from the authors’ graduate-level biostatistics course, Applied Categorical and Count Data Analysis explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors describe the basic ideas underlying each concept, model, and approach to give readers a good grasp of the fundamentals of the methodology without using rigorous mathematical arguments. The text covers classic concepts and popular topics, such as contingency tables, logistic models, and Poisson regression models, along with modern areas that include models for zero-modified count outcomes, parametric and semiparametric longitudinal data analysis, reliability analysis, and methods for dealing with missing values. R, SAS, SPSS, and Stata programming codes are provided for all the examples, enabling readers to immediately experiment with the data in the examples and even adapt or extend the codes to fit data from their own studies. Designed for a one-semester course for graduate and senior undergraduate students in biostatistics, this self-contained text is also suitable as a self-learning guide for biomedical and psychosocial researchers. It will help readers analyze data with discrete variables in a wide range of biomedical and psychosocial research fields.

Statistical Design and Analysis of Clinical Trials

Statistical Design and Analysis of Clinical Trials Author Weichung Joe Shih
ISBN-10 9781482250503
Release 2015-07-28
Pages 244
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Statistical Design and Analysis of Clinical Trials: Principles and Methods concentrates on the biostatistics component of clinical trials. Developed from the authors’ courses taught to public health and medical students, residents, and fellows during the past 15 years, the text shows how biostatistics in clinical trials is an integration of many fundamental scientific principles and statistical methods. Teach Your Students How to Design, Monitor, and Analyze Clinical Trials The book begins with ethical and safety principles, core trial design concepts, the principles and methods of sample size and power calculation, and analysis of covariance and stratified analysis. It then focuses on sequential designs and methods for two-stage Phase II cancer trials to Phase III group sequential trials, covering monitoring safety, futility, and efficacy. The authors also discuss the development of sample size reestimation and adaptive group sequential procedures, explain the concept of different missing data processes, and describe how to analyze incomplete data by proper multiple imputations. Turn Your Students into Better Clinical Trial Investigators This text reflects the academic research, commercial development, and public health aspects of clinical trials. It gives students a multidisciplinary understanding of the concepts and techniques involved in designing and analyzing various types of trials. The book’s balanced set of homework assignments and in-class exercises are appropriate for students in (bio)statistics, epidemiology, medicine, pharmacy, and public health.