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Confidence Intervals For Proportions And Related Measures Of Effect Size

Author : Robert G. Newcombe
ISBN : 9781439812785
Genre : Mathematics
File Size : 69.33 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, 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 : 66.57 MB
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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 : 41.74 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 : 59.38 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

Confidence Intervals

Author : Michael Smithson
ISBN : 076192499X
Genre : Mathematics
File Size : 59.92 MB
Format : PDF
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Using lots of easy to understand examples from different disciplines, the author introduces the basis of the confidence interval framework and provides the criteria for `best' confidence intervals, along with the trade-offs between confidence and precision. The book covers such pertinent topics as: the transformation principle whereby a confidence interval for a parameter may be used to construct an interval for any monotonic transformation of that parameter; confidence intervals on distributions whose shape changes with the value of the parameter being estimated; and, the relationship between confidence interval and significance testing frameworks, particularly regarding power.
Category: Mathematics

Primer On Effect Sizes Simple Research Designs And Confidence Intervals

Author : Marty Sapp
ISBN : 0398091978
Genre : Psychology
File Size : 34.5 MB
Format : PDF
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A Primer on Effect Sizes, Simple Research Designs, and Confidence Intervals was designed to help individuals learn to calculate effect sizes for their research designs. Effect sizes allow a clinician or researcher to determine the effect of a treatment. For example, an effect size of zero would indicate that the treatment had no effect, but generally effect sizes allow researchers to see the degree of effect of some treatment or intervention. Often, researchers and clinicians are not aware that effect sizes are connected to research designs. For years, statisticians have been aware of limits of null hypothesis significance testing (NHST). The Wilkinson Task Force (Wilkinson & Task Force on Statistical Inference, 1999) recommended that researchers report effect sizes and confidence intervals in addition to null hypothesis significance testing (NHST). The purpose of this book is to provide the connection among effect sizes, confidence intervals, and simple research designs. Also, some commonly used univariate and multivariate statistics are covered. Regression discontinuity designs, simple moderation and mediation designs, power analysis, and fit indices as effect sizes measure are presented. All calculations are demonstrated through a calculator and statistical packages such as Microsoft Excel, SPSS, SAS, Hayes' Process Analysis, and EQS. This book covers more than 25 effect sizes that are connected to simple research designs. It will be of interest to students taking a statistics class, research methods class, or research design class. Unlike many texts within this area, the current test will give students or researchers the understanding of how to calculate effect sizes with a simple calculator or with a few commands from statistical software programs. Hence, mathematical ability is not a prerequisite for this text. This text provides a nonmathematical treatment of effect sizes within the context of research designs. Finally, to aid understanding, critical material is repeated throughout this book.
Category: Psychology

Statistical Analysis Of Contingency Tables

Author : Morten Fagerland
ISBN : 9781315356556
Genre : Mathematics
File Size : 23.30 MB
Format : PDF
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Statistical Analysis of Contingency Tables is an invaluable tool for statistical inference in contingency tables. It covers effect size estimation, confidence intervals, and hypothesis tests for the binomial and the multinomial distributions, unpaired and paired 2x2 tables, rxc tables, ordered rx2 and 2xc tables, paired cxc tables, and stratified tables. For each type of table, key concepts are introduced, and a wide range of intervals and tests, including recent and unpublished methods and developments, are presented and evaluated. Topics such as diagnostic accuracy, inter-rater reliability, and missing data are also covered. The presentation is concise and easily accessible for readers with diverse professional backgrounds, with the mathematical details kept to a minimum. For more information, including a sample chapter and software, please visit the authors' website.
Category: Mathematics

Applied Meta Analysis With R

Author : Ding-Geng (Din) Chen
ISBN : 9781466505995
Genre : Mathematics
File Size : 81.63 MB
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In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data. Filling this knowledge gap, Applied Meta-Analysis with R shows how to implement statistical meta-analysis methods to real data using R. Drawing on their extensive research and teaching experiences, the authors provide detailed, step-by-step explanations of the implementation of meta-analysis methods using R. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R packages and functions. This systematic approach helps readers thoroughly understand the analysis methods and R implementation, enabling them to use R and the methods to analyze their own meta-data. Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R) in public health, medical research, governmental agencies, and the pharmaceutical industry.
Category: Mathematics

Statistics With Confidence

Author : Douglas Altman
ISBN : 9781118702505
Genre : Medical
File Size : 31.7 MB
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This highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.
Category: Medical

Sample Size Calculations In Clinical Research

Author : Shein-Chung Chow
ISBN : 0203911342
Genre : Mathematics
File Size : 69.53 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