Controlling The False Discovery Rate With Dynamic Adaptive Procedures And Of Grouped Hypotheses
Download Controlling The False Discovery Rate With Dynamic Adaptive Procedures And Of Grouped Hypotheses full books in PDF, epub, and Kindle. Read online free Controlling The False Discovery Rate With Dynamic Adaptive Procedures And Of Grouped Hypotheses ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author | : Yichuan Zhao |
Publisher | : Springer Nature |
Total Pages | : 506 |
Release | : 2021-10-14 |
Genre | : Medical |
ISBN | : 3030724379 |
This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data Clinical trials, FDR, and applications in health science Big network analytics and its applications in GWAS Survival analysis and functional data analysis Graphical modelling in genomic studies The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.
Author | : Daniel D. Suthers |
Publisher | : Springer Science & Business Media |
Total Pages | : 719 |
Release | : 2013-12-02 |
Genre | : Education |
ISBN | : 1461489601 |
The key idea of the book is that scientific and practical advances can be obtained if researchers working in traditions that have been assumed to be mutually incompatible make a real effort to engage in dialogue with each other, comparing and contrasting their understandings of a given phenomenon and how these different understandings can either complement or mutually elaborate on each other. This key idea applies to many fields, particularly in the social and behavioral sciences, as well as education and computer science. The book shows how we have achieved this by presenting our study of collaborative learning during the course of a four-year project. Through a series of five workshops involving dozens of researchers, the 37 editors and authors involved in this project studied and reported on collaborative learning, technology enhanced learning, and cooperative work. The authors share an interest in understanding group interactions, but approach this topic from a variety of traditional disciplinary homes and theoretical and methodological traditions. This allows the book to be of use to researchers in many different fields and with many different goals and agendas.
Author | : Siem Jan Koopman |
Publisher | : Emerald Group Publishing |
Total Pages | : 685 |
Release | : 2016-01-08 |
Genre | : Business & Economics |
ISBN | : 1785603523 |
This volume explores dynamic factor model specification, asymptotic and finite-sample behavior of parameter estimators, identification, frequentist and Bayesian estimation of the corresponding state space models, and applications.
Author | : Barbera, Elena |
Publisher | : IGI Global |
Total Pages | : 359 |
Release | : 2013-10-31 |
Genre | : Education |
ISBN | : 1466646527 |
For online learning and other forms of distance learning, time management is vital. As a recognized social asset, time constitutes a consistent and complete new approach to online higher education. Assessment and Evaluation of Time Factors in Online Teaching and Learning combines empirical and methodological research to study the role of time comprehensively from an institutional and management perspective, a technological perspective, and a pedagogical perspective. Focusing on higher education, this book is aimed at educational researchers, social science researchers, teachers, and students interested in improving the learning process and experience.
Author | : William D. Penny |
Publisher | : Elsevier |
Total Pages | : 689 |
Release | : 2011-04-28 |
Genre | : Psychology |
ISBN | : 0080466508 |
In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. - An essential reference and companion for users of the SPM software - Provides a complete description of the concepts and procedures entailed by the analysis of brain images - Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data - Stands as a compendium of all the advances in neuroimaging data analysis over the past decade - Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes - Structured treatment of data analysis issues that links different modalities and models - Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible
Author | : Alex Fornito |
Publisher | : Academic Press |
Total Pages | : 496 |
Release | : 2016-03-04 |
Genre | : Medical |
ISBN | : 0124081185 |
Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. - Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology - Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems - Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience - Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain
Author | : Somnath Datta |
Publisher | : Springer Nature |
Total Pages | : 349 |
Release | : 2021-10-27 |
Genre | : Medical |
ISBN | : 3030733513 |
Microbiome research has focused on microorganisms that live within the human body and their effects on health. During the last few years, the quantification of microbiome composition in different environments has been facilitated by the advent of high throughput sequencing technologies. The statistical challenges include computational difficulties due to the high volume of data; normalization and quantification of metabolic abundances, relative taxa and bacterial genes; high-dimensionality; multivariate analysis; the inherently compositional nature of the data; and the proper utilization of complementary phylogenetic information. This has resulted in an explosion of statistical approaches aimed at tackling the unique opportunities and challenges presented by microbiome data. This book provides a comprehensive overview of the state of the art in statistical and informatics technologies for microbiome research. In addition to reviewing demonstrably successful cutting-edge methods, particular emphasis is placed on examples in R that rely on available statistical packages for microbiome data. With its wide-ranging approach, the book benefits not only trained statisticians in academia and industry involved in microbiome research, but also other scientists working in microbiomics and in related fields.
Author | : Hamid R. Rabiee |
Publisher | : Frontiers Media SA |
Total Pages | : 361 |
Release | : 2023-01-27 |
Genre | : Science |
ISBN | : 2832510299 |
Author | : Amotz Zahavi |
Publisher | : Oxford University Press |
Total Pages | : 304 |
Release | : 1999-06-03 |
Genre | : Science |
ISBN | : 0190284587 |
Ever since Darwin, animal behavior has intrigued and perplexed human observers. The elaborate mating rituals, lavish decorative displays, complex songs, calls, dances and many other forms of animal signaling raise fascinating questions. To what degree can animals communicate within their own species and even between species? What evolutionary purpose do such communications serve? Perhaps most importantly, what can animal signaling tell us about our own non-verbal forms of communication? In The Handicap Principle, Amotz and Ashivag Zahavi offer a unifying theory that brilliantly explains many previously baffling aspects of animal signaling and holds up a mirror in which ordinary human behaviors take on surprising new significance. The wide-ranging implications of the Zahavis' new theory make it arguably the most important advance in animal behavior in decades. Based on 20 years of painstaking observation, the Handicap Principle illuminates an astonishing variety of signaling behaviors in animals ranging from ants and ameba to peacocks and gazelles. Essentially, the theory asserts that for animal signals to be effective they must be reliable, and to be reliable they must impose a cost, or handicap, on the signaler. When a gazelle sights a wolf, for instance, and jumps high into the air several times before fleeing, it is signaling, in a reliable way, that it is in tip-top condition, easily able to outrun the wolf. (A human parallel occurs in children's games of tag, where faster children will often taunt their pursuer before running). By momentarily handicapping itself--expending precious time and energy in this display--the gazelle underscores the truthfulness of its signal. Such signaling, the authors suggest, serves the interests of both predator and prey, sparing each the exhaustion of a pointless chase. Similarly, the enormous cost a peacock incurs by carrying its elaborate and weighty tail-feathers, which interfere with food gathering, reliably communicates its value as a mate able to provide for its offspring. Perhaps the book's most important application of the Handicap Principle is to the evolutionary enigma of animal altruism. The authors convincingly demonstrate that when an animal acts altruistically, it handicaps itself--assumes a risk or endures a sacrifice--not primarily to benefit its kin or social group but to increase its own prestige within the group and thus signal its status as a partner or rival. Finally, the Zahavis' show how many forms of non-verbal communication among humans can also be explained by the Handicap Principle. Indeed, the authors suggest that non-verbal signals--tones of voice, facial expressions, body postures--are quite often more reliable indicators of our intentions than is language. Elegantly written, exhaustively researched, and consistently enlivened by equal measures of insight and example, The Handicap Principle illuminates virtually every kind of animal communication. It not only allows us to hear what animals are saying to each other--and to understand why they are saying it--but also to see the enormously important role non-verbal behavior plays in human communication.
Author | : Michael A. Proschan |
Publisher | : CRC Press |
Total Pages | : 270 |
Release | : 2021-11-24 |
Genre | : Mathematics |
ISBN | : 1351673114 |
Statistical Thinking in Clinical Trials combines a relatively small number of key statistical principles and several instructive clinical trials to gently guide the reader through the statistical thinking needed in clinical trials. Randomization is the cornerstone of clinical trials and randomization-based inference is the cornerstone of this book. Read this book to learn the elegance and simplicity of re-randomization tests as the basis for statistical inference (the analyze as you randomize principle) and see how re-randomization tests can save a trial that required an unplanned, mid-course design change. Other principles enable the reader to quickly and confidently check calculations without relying on computer programs. The `EZ’ principle says that a single sample size formula can be applied to a multitude of statistical tests. The `O minus E except after V’ principle provides a simple estimator of the log odds ratio that is ideally suited for stratified analysis with a binary outcome. The same principle can be used to estimate the log hazard ratio and facilitate stratified analysis in a survival setting. Learn these and other simple techniques that will make you an invaluable clinical trial statistician.