A complete guide to the key statistical concepts essential for the design and construction of clinical trials As the newest major resource in the field of medical research, Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs presents a timely and authoritative reviewof the central statistical concepts used to build clinical trials that obtain the best results. The referenceunveils modern approaches vital to understanding, creating, and evaluating data obtained throughoutthe various stages of clinical trial design and analysis. Accessible and comprehensive, the first volume in a two-part set includes newly-written articles as well as established literature from the Wiley Encyclopedia of Clinical Trials. Illustrating a variety of statistical concepts and principles such as longitudinal data, missing data, covariates, biased-coin randomization, repeated measurements, and simple randomization, the book also provides in-depth coverage of the various trial designs found within phase I-IV trials. Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs also features: Detailed chapters on the type of trial designs, such as adaptive, crossover, group-randomized, multicenter, non-inferiority, non-randomized, open-labeled, preference, prevention, and superiority trials Over 100 contributions from leading academics, researchers, and practitioners An exploration of ongoing, cutting-edge clinical trials on early cancer and heart disease, mother-to-child human immunodeficiency virus transmission trials, and the AIDS Clinical Trials Group Methods and Applications of Statistics in Clinical Trials, Volume 1: Concepts, Principles, Trials, and Designs is an excellent reference for researchers, practitioners, and students in the fields of clinicaltrials, pharmaceutics, biostatistics, medical research design, biology, biomedicine, epidemiology,and public health.
Methods and Applications of Statistics in Clinical Trials,Volume 2: Planning, Analysis, and Inferential Methods includesupdates of established literature from the Wiley Encyclopedia ofClinical Trials as well as original material based on the latestdevelopments in clinical trials. Prepared by a leading expert, thesecond volume includes numerous contributions from currentprominent experts in the field of medical research. In addition,the volume features: • Multiple new articles exploring emerging topics, such asevaluation methods with threshold, empirical likelihood methods,nonparametric ROC analysis, over- and under-dispersed models, andmulti-armed bandit problems • Up-to-date research on the Cox proportional hazardmodel, frailty models, trial reports, intrarater reliability,conditional power, and the kappa index • Key qualitative issues including cost-effectivenessanalysis, publication bias, and regulatory issues, which arecrucial to the planning and data management of clinical trials
Facts101 is your complete guide to Methods and Applications of Statistics in Clinical Trials, Volume 2 - Planning, Analysis, and Inferential Methods. In this book, you will learn topics such as as those in your book plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.
Dieser Buchtitel ist Teil des Digitalisierungsprojekts Springer Book Archives mit Publikationen, die seit den Anfängen des Verlags von 1842 erschienen sind. Der Verlag stellt mit diesem Archiv Quellen für die historische wie auch die disziplingeschichtliche Forschung zur Verfügung, die jeweils im historischen Kontext betrachtet werden müssen. Dieser Titel erschien in der Zeit vor 1945 und wird daher in seiner zeittypischen politisch-ideologischen Ausrichtung vom Verlag nicht beworben.
This volume, representing a compilation of authoritative reviews on a multitude of uses of statistics in epidemiology and medical statistics written by internationally renowned experts, is addressed to statisticians working in biomedical and epidemiological fields who use statistical and quantitative methods in their work. While the use of statistics in these fields has a long and rich history, explosive growth of science in general and clinical and epidemiological sciences in particular have gone through a see of change, spawning the development of new methods and innovative adaptations of standard methods. Since the literature is highly scattered, the Editors have undertaken this humble exercise to document a representative collection of topics of broad interest to diverse users. The volume spans a cross section of standard topics oriented toward users in the current evolving field, as well as special topics in much need which have more recent origins. This volume was prepared especially keeping the applied statisticians in mind, emphasizing applications-oriented methods and techniques, including references to appropriate software when relevant. · Contributors are internationally renowned experts in their respective areas · Addresses emerging statistical challenges in epidemiological, biomedical, and pharmaceutical research · Methods for assessing Biomarkers, analysis of competing risks · Clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs · Structural equations modelling and longitudinal data analysis
Jianchang Lin,Bushi Wang,Xiaowen Hu,Kun Chen,Ray Liu
Selected Papers from the 2015 ICSA/Graybill Applied Statistics Symposium, Colorado State University, Fort Collins
Author: Jianchang Lin,Bushi Wang,Xiaowen Hu,Kun Chen,Ray Liu
The papers in this volume represent a broad, applied swath of advanced contributions to the 2015 ICSA/Graybill Applied Statistics Symposium of the International Chinese Statistical Association, held at Colorado State University in Fort Collins. The contributions cover topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. Each papers was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe.
This IMA Volume in Mathematics and its Applications STATISTICAL MODELS IN EPIDEMIOLOGY, THE ENVIRONMENT,AND CLINICAL TRIALS is a combined proceedings on "Design and Analysis of Clinical Trials" and "Statistics and Epidemiology: Environment and Health. " This volume is the third series based on the proceedings of a very successful 1997 IMA Summer Program on "Statistics in the Health Sciences. " I would like to thank the organizers: M. Elizabeth Halloran of Emory University (Biostatistics) and Donald A. Berry of Duke University (Insti tute of Statistics and Decision Sciences and Cancer Center Biostatistics) for their excellent work as organizers of the meeting and for editing the proceedings. I am grateful to Seymour Geisser of University of Minnesota (Statistics), Patricia Grambsch, University of Minnesota (Biostatistics); Joel Greenhouse, Carnegie Mellon University (Statistics); Nicholas Lange, Harvard Medical School (Brain Imaging Center, McLean Hospital); Barry Margolin, University of North Carolina-Chapel Hill (Biostatistics); Sandy Weisberg, University of Minnesota (Statistics); Scott Zeger, Johns Hop kins University (Biostatistics); and Marvin Zelen, Harvard School of Public Health (Biostatistics) for organizing the six weeks summer program. I also take this opportunity to thank the National Science Foundation (NSF) and the Army Research Office (ARO), whose financial support made the workshop possible. Willard Miller, Jr.
Statistical methods have become an increasingly important and integral part of research in the health sciences. Many sophisticated methodologies have been developed for specific applications and problems. This self-contained comprehensive volume covers a wide range of topics pertaining to new statistical methods in the health sciences, including epidemiology, pharmacovigilance, quality of life, survival analysis, and genomics. The book will serve the health science community as well as practitioners, researchers, and graduate students in applied probability, statistics, and biostatistics.
A new edition of the classic guide to the use of statistics inmedicine, featuring examples from articles in the New EnglandJournal of Medicine Medical Uses of Statistics has served as one of the mostinfluential works on the subject for physicians,physicians-in-training, and a myriad of healthcare experts who needa clear idea of the proper application of statistical techniques inclinical studies as well as the implications of theirinterpretation for clinical practice. This Third Editionmaintains the focus on the critical ideas, rather than themechanics, to give practitioners and students the resources theyneed to understand the statistical methods they encounter in modernmedical literature. Bringing together contributions from more than two dozendistinguished statisticians and medical doctors, this volumestresses the underlying concepts in areas such as randomizedtrials, survival analysis, genetics, linear regression,meta-analysis, and risk analysis. The Third Editionincludes: Numerous examples based on studies taken directly from the pagesof the New England Journal ofMedicine Two added chapters on statistics in genetics Two new chapters on the application of statistical methods tostudies in epidemiology New chapters on analyses of randomized trials, linearregression, categorical data analysis, meta-analysis, subgroupanalyses, and risk analysis Updated chapters on statistical thinking, crossover designs,p-values, survival analysis, and reporting research results A focus on helping readers to critically interpret publishedresults of clinical research Medical Uses of Statistics, Third Edition is a valuableresource for researchers and physicians working in anyhealth-related field. It is also an excellent supplemental book forcourses on medicine, biostatistics, and clinical research at theupper-undergraduate and graduate levels. You can also visit the NewEngland Journal of Medicine website for relatedinformation.
Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simple application of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data) have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2) high-level complexity of data because they are longitudinal, incomplete, or latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reduction impossible, or because of extremely small or large size; and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face. This book is written for researchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce modern methods in biostatistics and help researchers and students quickly grasp key concepts and methods. Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed in this single volume.
The Tutorials in Biostatistics have become a very popular feature of the prestigious Wiley journal, Statistics in Medicine (SIM). The introductory style and practical focus make them accessible to a wide audience including medical practitioners with limited statistical knowledge. This book represents the first of two volumes presenting the best tutorials published in SIM, focusing on statistical methods in clinical studies. Topics include the design and analysis of clinical trials, epidemiology, survival analysis, and data monitoring. Each tutorial is focused on a medical problem, has been fully peer-reviewed and edited, and is authored by leading researchers in biostatistics. Many articles include an appendix on the latest developments since publication in the journal and additional references. This will appeal to statisticians working in medical research, as well as statistically-minded clinicians, biologists, epidemiologists and geneticists. It will also appeal to graduate students of biostatistics.
The book aims to provide both comprehensive reviews of the classical methods and an introduction to new developments in medical statistics. The topics range from meta analysis, clinical trial design, causal inference, personalized medicine to machine learning and next generation sequence analysis. Since the publication of the first edition, there have been tremendous advances in biostatistics and bioinformatics. The new edition tries to cover as many important emerging areas and reflect as much progress as possible. Many distinguished scholars, who greatly advanced their research areas in statistical methodology as well as practical applications, also have revised several chapters with relevant updates and written new ones from scratch. The new edition has been divided into four sections, including, Statistical Methods in Medicine and Epidemiology, Statistical Methods in Clinical Trials, Statistical Genetics, and General Methods. To reflect the rise of modern statistical genetics as one of the most fertile research areas since the publication of the first edition, the brand new section on Statistical Genetics includes entirely new chapters reflecting the state of the art in the field. Although tightly related, all the book chapters are self-contained and can be read independently. The book chapters intend to provide a convenient launch pad for readers interested in learning a specific topic, applying the related statistical methods in their scientific research and seeking the newest references for in-depth research. Contents:Statistics in Medicine and Epidemiology:History of Statistical Thinking in Medicine (Tar Timothy Chen)Describing Data, Modeling Variation, and Statistical Practice (Hongyan Du and Ming T Tan)Covariate-Specific and Covariate-Adjusted Predictive Values of Prognostic Biomarkers with Survival Outcome (Yunbei Ma, Xiao-Hua Zhou and Kwun Chuen (Gary) Chan)Statistical Methods for Personalized Medicine (Lu Tian and Xiaoguang Zhao)Statistics Used in Quality Control, Quality Assurance, and Quality Improvement in Radiological Studies (Ying Lu and Shoujun Zhao)Applications of Statistical Methods in Medical Imaging (Jesse S Jin)Cost-Effectiveness Analysis and Evidence-Based Medicine (Jianli Li)Quality of Life: Issues Concerning Assessment and Analysis (Jiqian Fang and Yuantao Hao)Meta-Analysis (Xuyu Zhou, Jiqian Fang, Chuanhua Yu, Zongli Xu, Lu Tian, and Ying Lu)Statistical Models and Methods in Infectious Diseases (Hulin Wu and Shoujun Zhao)Special Models for Sampling Survey (Sujuan Gao)The Use of Capture–Recapture Methodology in Epidemiological Surveillance and Ecological Surveys (Anne Chao, T C Hsieh and Hsin-Chou Yang)Statistical Methods in the Effective Evaluation of Mass Screening for Diseases (Qing Liu)Statistics in Clinical Trials:Statistics in Biopharmaceutical Research and Development (Shein-Chung Chow and Annpey Pong)Statistics in Pharmacology and Pre-Clinical Studies (Tze Leung Lai, Mei-Chiung Shin and Guangrui Zhu)Statistics in Toxicology (James J Chen)Dose-Response Modeling and Benchmark Doses in Health Risk Assessment (Yiliang Zhu)Some Fundamental Statistical Issues and Methodologies in Confirmatory Trials (George Y H Chi, Haiyan Xu and Qing Liu)Surrogates for Qualitative Evaluation of Treatment Effects (Zhi Geng)Adaptive Trial Design in Clinical Research (Annpey Pong and Shein-Chung Chow)Statistics in the Research of Traditional Chinese Medicine (Danhui Yi and Yang Li)Statistical Genetics:Sparse Segment Identifications with Applications to DNA Copy Number Variation Analysis (X Jessie Jeng, T Tony Cai and Hongzhe Li)Statistical Methods for Design and Analysis of Linkage Studies (Qizhai Li, Hong Qin, Zhaohai Li, and Gang Zheng)Transcriptome Analysis Using Next-Generation Sequencing (Jingyi Jessica Li, Haiyan Huang, Minping Qian and Xuegong Zhang)Genetic Structure of Human Population (Hua Tang and Kun Tang)Data Integration Methods in Genome Wide Association Studies (Ning Sun and Hongyu Zhao)Causal Inference (Zhi Geng)General Methods:Survival Analysis (D Y Lin)Nonparametric Regression Models for the Analysis of Longitudinal Data (Colin O Wu, Xin Tian, Kai F Yu, and Mi-Xia Wu)Local Modeling: Density Estimation and Nonparametric Regression (Jianqing Fan and Runze Li)Statistical Methods for Dependent Data (Feng Chen)Bayesian Methods (Ming-Hui Chen and Keying Ye)Valid Prior-Free Probabilistic Inference and Its Applications in Medical Statistics (Duncan Ermini Leaf, Hyokun Yun, and Chuanhai Liu)Stochastic Processes and Their Applications in Medical Science (Caixia Li and Jiqian Fang)Interpolation of Missing Values and Adjustment of Moving Holiday Effect in Time Series (Zhang Jin-Xin, Zhang Xi, Xue Yun-Lian, Li Ji-Bin and Huang Bo)Tree-based Methods (Heping Zhang)Introduction to Artificial Neural Networks (Xia Jielai, Jiang Hongwei, and Tang Qiyi) Readership: Biostatisticians, applied statisticians, medical researchers and clinicians, biopharmaceutical researchers, public health epidemiologists, biometricians and applied mathematicians. Key Features: The book covers very broad topics in medical statistics The book covers both most recent developments as well as classical work of the selected areas The book chapter is written by the experts in the field and illustrated with real life examplesKeywords:Medicine;Statistics;Epidemiology;Genomics;Clinical Trials;Bioinformatics;Machine Learning;Statistical Theory;Public HealthReviews: Review of the First Edition: “Overall the book covers a wide variety of applications. Each method is presented in sufficient depth to allow the reader to understand when the method(s) can be used … this book would be a useful resource for any practitioner in medical research.” Statistical Methods in Medical Research
Author: Mounir Mesbah,Bernard F. Cole,Mei-Ling Ting Lee
Publisher: Springer Science & Business Media
On October 16 and 17, 2000, we hosted an international workshop entitled "Statistical Design, Measurement, and Analysis of Health Related Quality of Life." The workshop was held in the beautiful city of Arradon, South Brittany, France with the main goal of fostering an interdisciplinary forum for discussion of theoretical and applied statistical issues arising in studies of health-related quality of life (HRQoL). Included were biostatisticians, psychometricians and public health professionals (e.g., physicians, sociologists, psychologists) active in the study ofHRQoL. In assembling this volume, we invited each conference participant to contribute a paper based on his or her presentation and the ensuing and very interesting discussions that took place in Arradon. All papers were peer-reviewed, by anonymous reviewers, and revised before final editing and acceptance. Although this process was quite time consuming, we believe that it greatly improved the volume as a whole, making this book a valuable contribution to the field ofHRQoL research. The volume presents a broad spectrum of papers presented at the Workshop, and thus illustrates the range of current research related to the theory, methods and applications of HRQoL, as well as the interdisciplinary nature ofthis work. Following an introduction written by Sir David Cox, it includes 27 articles organized into the following chapters.
Eulers Konstante, Primzahlstrände und die Riemannsche Vermutung
Author: Julian Havil
Jeder kennt p = 3,14159..., viele kennen e = 2,71828..., einige i. Und dann? Die "viertwichtigste" Konstante ist die Eulersche Zahl g = 0,5772156... - benannt nach dem genialen Leonhard Euler (1707-1783). Bis heute ist unbekannt, ob g eine rationale Zahl ist. Das Buch lotet die "obskure" Konstante aus. Die Reise beginnt mit Logarithmen und der harmonischen Reihe. Es folgen Zeta-Funktionen und Eulers wunderbare Identität, Bernoulli-Zahlen, Madelungsche Konstanten, Fettfinger in Wörterbüchern, elende mathematische Würmer und Jeeps in der Wüste. Besser kann man nicht über Mathematik schreiben. Was Julian Havil dazu zu sagen hat, ist spektakulär.
The Tutorials in Biostatistics have become a very popular feature of the prestigious Wiley journal, Statistics in Medicine (SIM). The introductory style and practical focus make them accessible to a wide audience including medical practitioners with limited statistical knowledge. This book represents the second of two volumes presenting the best tutorials published in SIM, focusing on statistical modeling of complex data. Topics include clustered data, hierarchical models, mixed models, genetic modeling, and meta-analysis. Each tutorial is focused on a medical problem, has been fully peer-reviewed and edited, and is authored by leading researchers in biostatistics. Many articles include an appendix on the latest developments since publication in the journal and additional references. This will appeal to statisticians working in medical research, as well as statistically-minded clinicians, biologists, epidemiologists and geneticists. It will also appeal to graduate students of biostatistics.
Author: Karl E. Peace,Ding-Geng Chen,Sandeep Menon
This BASS book Series publishes selected high-quality papers reflecting recent advances in the design and biostatistical analysis of biopharmaceutical experiments – particularly biopharmaceutical clinical trials. The papers were selected from invited presentations at the Biopharmaceutical Applied Statistics Symposium (BASS), which was founded by the first Editor in 1994 and has since become the premier international conference in biopharmaceutical statistics. The primary aims of the BASS are: 1) to raise funding to support graduate students in biostatistics programs, and 2) to provide an opportunity for professionals engaged in pharmaceutical drug research and development to share insights into solving the problems they encounter.The BASS book series is initially divided into three volumes addressing: 1) Design of Clinical Trials; 2) Biostatistical Analysis of Clinical Trials; and 3) Pharmaceutical Applications. This book is the first of the 3-volume book series. The topics covered include: A Statistical Approach to Clinical Trial Simulations, Comparison of Statistical Analysis Methods Using Modeling and Simulation for Optimal Protocol Design, Adaptive Trial Design in Clinical Research, Best Practices and Recommendations for Trial Simulations in the Context of Designing Adaptive Clinical Trials, Designing and Analyzing Recurrent Event Data Trials, Bayesian Methodologies for Response-Adaptive Allocation, Addressing High Placebo Response in Neuroscience Clinical Trials, Phase I Cancer Clinical Trial Design: Single and Combination Agents, Sample Size and Power for the Mixed Linear Model, Crossover Designs in Clinical Trials, Data Monitoring: Structure for Clinical Trials and Sequential Monitoring Procedures, Design and Data Analysis for Multiregional Clinical Trials – Theory and Practice, Adaptive Group-Sequential Multi-regional Outcome Studies in Vaccines, Development and Validation of Patient-reported Outcomes, Interim Analysis of Survival Trials: Group Sequential Analyses, and Conditional Power – A Non-proportional Hazards Perspective.
Atanu Biswas,Sujay Datta,Jason P. Fine,Mark R. Segal
Clinical Trials, Epidemiology, Survival Analysis, and Bioinformatics
Author: Atanu Biswas,Sujay Datta,Jason P. Fine,Mark R. Segal
Publisher: John Wiley & Sons
The Most Comprehensive and Cutting-Edge Guide to Statistical Applications in Biomedical Research With the increasing use of biotechnology in medical research and the sophisticated advances in computing, it has become essential for practitioners in the biomedical sciences to be fully educated on the role statistics plays in ensuring the accurate analysis of research findings. Statistical Advances in the Biomedical Sciences explores the growing value of statistical knowledge in the management and comprehension of medical research and, more specifically, provides an accessible introduction to the contemporary methodologies used to understand complex problems in the four major areas of modern-day biomedical science: clinical trials, epidemiology, survival analysis, and bioinformatics. Composed of contributions from eminent researchers in the field, this volume discusses the application of statistical techniques to various aspects of modern medical research and illustrates how these methods ultimately prove to be an indispensable part of proper data collection and analysis. A structural uniformity is maintained across all chapters, each beginning with an introduction that discusses general concepts and the biomedical problem under focus and is followed by specific details on the associated methods, algorithms, and applications. In addition, each chapter provides a summary of the main ideas and offers a concluding remarks section that presents novel ideas, approaches, and challenges for future research. Complete with detailed references and insight on the future directions of biomedical research, Statistical Advances in the Biomedical Sciences provides vital statistical guidance to practitioners in the biomedical sciences while also introducing statisticians to new, multidisciplinary frontiers of application. This text is an excellent reference for graduate- and PhD-level courses in various areas of biostatistics and the medical sciences and also serves as a valuable tool for medical researchers, statisticians, public health professionals, and biostatisticians.
Praise for the Second Edition: “...a grand feast for biostatisticians. It stands readyto satisfy the appetite of any pharmaceutical scientist with arespectable statistical appetite.” —Journal of ClinicalResearch Best Practices The Third Edition of Design and Analysis of ClinicalTrials provides complete, comprehensive, and expanded coverageof recent health treatments and interventions. Featuring a unifiedpresentation, the book provides a well-balanced summary of currentregulatory requirements and recently developed statistical methodsas well as an overview of the various designs and analyses that areutilized at different stages of clinical research and development.Additional features of this Third Edition include: • New chapters on biomarker development and targetclinical trials, adaptive design, trials for evaluating diagnosticdevices, statistical methods for translational medicine, andtraditional Chinese medicine • A balanced overview of current and emerging clinicalissues as well as newly developed statistical methodologies • Practical examples of clinical trials that demonstrateeveryday applicability, with illustrations and examples to explainkey concepts • New sections on bridging studies and global trials, QTstudies, multinational trials, comparative effectiveness trials,and the analysis of QT/QTc prolongation • A complete and balanced presentation of clinical andscientific issues, statistical concepts, and methodologies forbridging clinical and statistical disciplines • An update of each chapter that reflects changes inregulatory requirements for the drug review and approval processand recent developments in statistical design and methodology forclinical research and development Design and Analysis of Clinical Trials, Third Editioncontinues to be an ideal clinical research reference for academic,pharmaceutical, medical, and regulatory scientists/researchers,statisticians, and graduate-level students.
Epidemiologic studies provide research strategies for investigating public health and scientific questions relating to the factors that cause and prevent ailments in human populations. Statistics in Epidemiology: Methods, Techniques and Applications presents a comprehensive review of the wide range of principles, methods and techniques underlying prospective, retrospective and cross-sectional approaches to epidemiologic studies. Written for epidemiologists and other researchers without extensive backgrounds in statistics, this new book provides a clear and concise description of the statistical tools used in epidemiology. Emphasis is given to the application of these statistical tools, and examples are provided to illustrate direct methods for applying common statistical techniques in order to obtain solutions to problems. Statistics in Epidemiology: Methods, Techniques and Applications goes beyond the elementary material found in basic epidemiology and biostatistics books and provides a detailed account of techniques: