CONFIDENCE INTERVALS FOR PROPORTIONS AND RELATED MEASURES OF EFFECT SIZE CHAPMAN HALL CRC BIOSTATISTICS SERIES

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Confidence Intervals For Proportions And Related Measures Of Effect Size

Author : Robert G. Newcombe
ISBN : 9781439812785
Genre : Mathematics
File Size : 22.87 MB
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Confidence Intervals for Proportions and Related Measures of Effect Size illustrates the use of effect size measures and corresponding confidence intervals as more informative alternatives to the most basic and widely used significance tests. The book provides you with a deep understanding of what happens when these statistical methods are applied in situations far removed from the familiar Gaussian case. Drawing on his extensive work as a statistician and professor at Cardiff University School of Medicine, the author brings together methods for calculating confidence intervals for proportions and several other important measures, including differences, ratios, and nonparametric effect size measures generalizing Mann-Whitney and Wilcoxon tests. He also explains three important approaches to obtaining intervals for related measures. Many examples illustrate the application of the methods in the health and social sciences. Requiring little computational skills, the book offers user-friendly Excel spreadsheets for download at www.crcpress.com, enabling you to easily apply the methods to your own empirical data.
Category: Mathematics

Applied Statistical Inference

Author : Leonhard Held
ISBN : 9783642378874
Genre : Mathematics
File Size : 52.31 MB
Format : PDF
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This book covers modern statistical inference based on likelihood with applications in medicine, epidemiology and biology. Two introductory chapters discuss the importance of statistical models in applied quantitative research and the central role of the likelihood function. The rest of the book is divided into three parts. The first describes likelihood-based inference from a frequentist viewpoint. Properties of the maximum likelihood estimate, the score function, the likelihood ratio and the Wald statistic are discussed in detail. In the second part, likelihood is combined with prior information to perform Bayesian inference. Topics include Bayesian updating, conjugate and reference priors, Bayesian point and interval estimates, Bayesian asymptotics and empirical Bayes methods. Modern numerical techniques for Bayesian inference are described in a separate chapter. Finally two more advanced topics, model choice and prediction, are discussed both from a frequentist and a Bayesian perspective. A comprehensive appendix covers the necessary prerequisites in probability theory, matrix algebra, mathematical calculus, and numerical analysis.
Category: Mathematics

Randomized Phase Ii Cancer Clinical Trials

Author : Sin-Ho Jung
ISBN : 9781439871850
Genre : Mathematics
File Size : 86.69 MB
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In cancer research, a traditional phase II trial is designed as a single-arm trial that compares the experimental therapy to a historical control. This simple trial design has led to several adverse issues, including increased false positivity of phase II trial results and negative phase III trials. To rectify these problems, oncologists and biostatisticians have begun to use a randomized phase II trial that compares an experimental therapy with a prospective control therapy. Randomized Phase II Cancer Clinical Trials explains how to properly select and accurately use diverse statistical methods for designing and analyzing phase II trials. The author first reviews the statistical methods for single-arm phase II trials since some methodologies for randomized phase II trials stem from single-arm phase II trials and many phase II cancer clinical trials still use single-arm designs. The book then presents methods for randomized phase II trials and describes statistical methods for both single-arm and randomized phase II trials. Although the text focuses on phase II cancer clinical trials, the statistical methods covered can also be used (with minor modifications) in phase II trials for other diseases and in phase III cancer clinical trials. Suitable for cancer clinicians and biostatisticians, this book shows how randomized phase II trials with a prospective control resolve the shortcomings of traditional single-arm phase II trials. It provides readers with numerous statistical design and analysis methods for randomized phase II trials in oncology.
Category: Mathematics

Optimal Design For Nonlinear Response Models

Author : Valerii V. Fedorov
ISBN : 9781439821510
Genre : Mathematics
File Size : 64.76 MB
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Optimal Design for Nonlinear Response Models discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies. The book draws on the authors’ many years of experience in academia and the pharmaceutical industry. While the focus is on nonlinear models, the book begins with an explanation of the key ideas, using linear models as examples. Applying the linearization in the parameter space, it then covers nonlinear models and locally optimal designs as well as minimax, optimal on average, and Bayesian designs. The authors also discuss adaptive designs, focusing on procedures with non-informative stopping. The common goals of experimental design—such as reducing costs, supporting efficient decision making, and gaining maximum information under various constraints—are often the same across diverse applied areas. Ethical and regulatory aspects play a much more prominent role in biological, medical, and pharmaceutical research. The authors address all of these issues through many examples in the book.
Category: Mathematics

Sample Size Calculations In Clinical Research

Author : Shein-Chung Chow
ISBN : 0203911342
Genre : Mathematics
File Size : 69.15 MB
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Sample size calculation plays an important role in clinical research. It is not uncommon, however, to observe discrepancies among study objectives (or hypotheses), study design, statistical analysis (or test statistic), and sample size calculation. Focusing on sample size calculation for studies conducted during the various phases of clinical research and development, Sample Size Calculation in Clinical Research explores the causes of discrepancies and how to avoid them. This volume provides formulas and procedures for determination of sample size required not only for testing equality, but also for testing non-inferiority/superiority, and equivalence (similarity) based on both untransformed (raw) data and log-transformed data under a parallel-group design or a crossover design with equal or unequal ratio of treatment allocations. It contains a comprehensive and unified presentation of statistical procedures for sample size calculation that are commonly employed at various phases of clinical development. Each chapter includes, whenever possible, real examples of clinical studies from therapeutic areas such as cardiovascular, central nervous system, anti-infective, oncology, and women's health to demonstrate the clinical and statistical concepts, interpretations, and their relationships and interactions. The book highlights statistical procedures for sample size calculation and justification that are commonly employed in clinical research and development. It provides clear, illustrated explanations of how the derived formulas and/or statistical procedures can be used.
Category: Mathematics

Medical Biostatistics Second Edition

Author : Abhaya Indrayan
ISBN : 9781584888888
Genre : Mathematics
File Size : 89.58 MB
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Emphasizing statistical concepts used in medicine, the interpretation of methods, and applications, Medical Biostatistics, Second Edition shows how biostatistical methods are important tools in managing uncertainties in medicine and the health sciences. With coverage ranging from elementary topics, such as mean and standard deviation, to advanced approaches, such as logistic regression and multivariate methods, this edition is even more far-reaching in scope than its predecessor. New to the Second Edition Full chapters on clinical trials, observational studies, laboratory experiments, survival analysis, and logistic regression A new chapter on clinimetrics and evidence-based medicine Expanded discussions on epistemic uncertainties, crossover designs, equivalence trials and studies, hazard functions, and the log-rank test The introduction of research evidence, multilevel regression, classification, and regression trees at an elementary level Sample size formulas for relative risk, odds ratio, and survival studies Numerous additional examples from contemporary medical literature Numbered steps for the many procedures and remarks Requiring only high school algebra, this text enables a solid understanding of the statistical concepts required to critically examine medical literature, scientifically plan and carry out medical investigations, and meaningfully analyze data.
Category: Mathematics

Medical Biostatistics Fourth Edition

Author : Abhaya Indrayan
ISBN : 9781498799546
Genre : Mathematics
File Size : 89.14 MB
Format : PDF
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Encyclopedic in breadth, yet practical and concise, Medical Biostatistics, Fourth Edition focuses on the statistical aspects ofmedicine with a medical perspective, showing the utility of biostatistics as a tool to manage many medical uncertainties. This edition includes more topics in order to fill gaps in the previous edition. Various topics have been enlarged and modified as per the new understanding of the subject.
Category: Mathematics

Cluster Randomised Trials Second Edition

Author : Richard J. Hayes
ISBN : 9781315353234
Genre : Mathematics
File Size : 50.94 MB
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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.
Category: Mathematics

Biostatistics A Computing Approach

Author : Stewart Anderson
ISBN : 9781439897904
Genre : Mathematics
File Size : 23.89 MB
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The emergence of high-speed computing has facilitated the development of many exciting statistical and mathematical methods in the last 25 years, broadening the landscape of available tools in statistical investigations of complex data. Biostatistics: A Computing Approach focuses on visualization and computational approaches associated with both modern and classical techniques. Furthermore, it promotes computing as a tool for performing both analyses and simulations that can facilitate such understanding. As a practical matter, programs in R and SAS are presented throughout the text. In addition to these programs, appendices describing the basic use of SAS and R are provided. Teaching by example, this book emphasizes the importance of simulation and numerical exploration in a modern-day statistical investigation. A few statistical methods that can be implemented with simple calculations are also worked into the text to build insight about how the methods really work. Suitable for students who have an interest in the application of statistical methods but do not necessarily intend to become statisticians, this book has been developed from Introduction to Biostatistics II, which the author taught for more than a decade at the University of Pittsburgh.
Category: Mathematics