Computational And Methodological Statistics And Biostatistics

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Computational and Methodological Statistics and Biostatistics

Andriëtte Bekker,(Din) Ding-Geng Chen,Johannes T. Ferreira
Computational and Methodological Statistics and Biostatistics Book PDF

Author : Andriëtte Bekker,(Din) Ding-Geng Chen,Johannes T. Ferreira
Publisher : Springer Nature
Page : 543 pages
File Size : 47,6 Mb
Release : 2020-08-10
Category : Medical
ISBN : 9783030421960

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Computational and Methodological Statistics and Biostatistics by Andriëtte Bekker,(Din) Ding-Geng Chen,Johannes T. Ferreira Pdf

In the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes. Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and biostatisticians and provides an array of thought processes and tools to its readers. The book thereby creates an understanding and appreciation of recent developments as well as an implementation of these contributions within the broader framework of both academia and industry. Computational and Methodological Statistics and Biostatistics is composed of three main themes: • Recent developments in theory and applications of statistical distributions;• Recent developments in supervised and unsupervised modelling;• Recent developments in biostatistics; and also features programming code and accompanying algorithms to enable readers to replicate and implement methodologies. Therefore, this monograph provides a concise point of reference for a variety of current trends and topics within the statistical domain. With interdisciplinary appeal, it will be useful to researchers, graduate students, and practitioners in statistics, biostatistics, clinical methodology, geology, data science, and actuarial science, amongst others.

Advances in Complex Data Modeling and Computational Methods in Statistics

Anna Maria Paganoni,Piercesare Secchi
Advances in Complex Data Modeling and Computational Methods in Statistics Book PDF

Author : Anna Maria Paganoni,Piercesare Secchi
Publisher : Springer
Page : 210 pages
File Size : 55,9 Mb
Release : 2014-11-04
Category : Mathematics
ISBN : 9783319111490

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Advances in Complex Data Modeling and Computational Methods in Statistics by Anna Maria Paganoni,Piercesare Secchi Pdf

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held at the Politecnico di Milano, 2013. All the papers published here have been rigorously peer-reviewed.

Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates

Jeffrey R. Wilson,Elsa Vazquez-Arreola,(Din) Ding-Geng Chen
Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates Book PDF

Author : Jeffrey R. Wilson,Elsa Vazquez-Arreola,(Din) Ding-Geng Chen
Publisher : Springer Nature
Page : 182 pages
File Size : 54,6 Mb
Release : 2020-09-28
Category : Medical
ISBN : 9783030489045

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Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates by Jeffrey R. Wilson,Elsa Vazquez-Arreola,(Din) Ding-Geng Chen Pdf

This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars. While the models presented in the volume are applied to health and health-related data, they can be used to analyze any kind of data that contain covariates that change over time. The included data are analyzed with the use of both R and SAS, and the data and computing programs are provided to readers so that they can replicate and implement covered methods. It is an excellent resource for scholars of both computational and methodological statistics and biostatistics, particularly in the applied areas of health. ​

Statistics in the Health Sciences

Albert Vexler,Alan Hutson
Statistics in the Health Sciences Book PDF

Author : Albert Vexler,Alan Hutson
Publisher : CRC Press
Page : 298 pages
File Size : 54,9 Mb
Release : 2018-01-19
Category : Mathematics
ISBN : 9781315293752

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Statistics in the Health Sciences by Albert Vexler,Alan Hutson Pdf

"This very informative book introduces classical and novel statistical methods that can be used by theoretical and applied biostatisticians to develop efficient solutions for real-world problems encountered in clinical trials and epidemiological studies. The authors provide a detailed discussion of methodological and applied issues in parametric, semi-parametric and nonparametric approaches, including computationally extensive data-driven techniques, such as empirical likelihood, sequential procedures, and bootstrap methods. Many of these techniques are implemented using popular software such as R and SAS."— Vlad Dragalin, Professor, Johnson and Johnson, Spring House, PA "It is always a pleasure to come across a new book that covers nearly all facets of a branch of science one thought was so broad, so diverse, and so dynamic that no single book could possibly hope to capture all of the fundamentals as well as directions of the field. The topics within the book’s purview—fundamentals of measure-theoretic probability; parametric and non-parametric statistical inference; central limit theorems; basics of martingale theory; Monte Carlo methods; sequential analysis; sequential change-point detection—are all covered with inspiring clarity and precision. The authors are also very thorough and avail themselves of the most recent scholarship. They provide a detailed account of the state of the art, and bring together results that were previously scattered across disparate disciplines. This makes the book more than just a textbook: it is a panoramic companion to the field of Biostatistics. The book is self-contained, and the concise but careful exposition of material makes it accessible to a wide audience. This is appealing to graduate students interested in getting into the field, and also to professors looking to design a course on the subject." — Aleksey S. Polunchenko, Department of Mathematical Sciences, State University of New York at Binghamton This book should be appropriate for use both as a text and as a reference. This book delivers a "ready-to-go" well-structured product to be employed in developing advanced courses. In this book the readers can find classical and new theoretical methods, open problems and new procedures. The book presents biostatistical results that are novel to the current set of books on the market and results that are even new with respect to the modern scientific literature. Several of these results can be found only in this book.

Innovations in Multivariate Statistical Modeling

Andriëtte Bekker,Johannes T. Ferreira,Mohammad Arashi,Ding-Geng Chen
Innovations in Multivariate Statistical Modeling Book PDF

Author : Andriëtte Bekker,Johannes T. Ferreira,Mohammad Arashi,Ding-Geng Chen
Publisher : Springer Nature
Page : 434 pages
File Size : 49,9 Mb
Release : 2022-12-15
Category : Mathematics
ISBN : 9783031139710

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Innovations in Multivariate Statistical Modeling by Andriëtte Bekker,Johannes T. Ferreira,Mohammad Arashi,Ding-Geng Chen Pdf

Multivariate statistical analysis has undergone a rich and varied evolution during the latter half of the 20th century. Academics and practitioners have produced much literature with diverse interests and with varying multidisciplinary knowledge on different topics within the multivariate domain. Due to multivariate algebra being of sustained interest and being a continuously developing field, its appeal breaches laterally across multiple disciplines to act as a catalyst for contemporary advances, with its core inferential genesis remaining in that of statistics. It is exactly this varied evolution caused by an influx in data production, diffusion, and understanding in scientific fields that has blurred many lines between disciplines. The cross-pollination between statistics and biology, engineering, medical science, computer science, and even art, has accelerated the vast amount of questions that statistical methodology has to answer and report on. These questions are often multivariate in nature, hoping to elucidate uncertainty on more than one aspect at the same time, and it is here where statistical thinking merges mathematical design with real life interpretation for understanding this uncertainty. Statistical advances benefit from these algebraic inventions and expansions in the multivariate paradigm. This contributed volume aims to usher novel research emanating from a multivariate statistical foundation into the spotlight, with particular significance in multidisciplinary settings. The overarching spirit of this volume is to highlight current trends, stimulate a focus on, and connect multidisciplinary dots from and within multivariate statistical analysis. Guided by these thoughts, a collection of research at the forefront of multivariate statistical thinking is presented here which has been authored by globally recognized subject matter experts.

Computational Intelligence Methods for Bioinformatics and Biostatistics

Andrea Bracciali,Giulio Caravagna,David Gilbert,Roberto Tagliaferri
Computational Intelligence Methods for Bioinformatics and Biostatistics Book PDF

Author : Andrea Bracciali,Giulio Caravagna,David Gilbert,Roberto Tagliaferri
Publisher : Springer
Page : 249 pages
File Size : 50,9 Mb
Release : 2017-10-14
Category : Computers
ISBN : 9783319678344

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Computational Intelligence Methods for Bioinformatics and Biostatistics by Andrea Bracciali,Giulio Caravagna,David Gilbert,Roberto Tagliaferri Pdf

This book constitutes the thoroughly refereed post-conference proceedings of the 13th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2016, held in Stirling, UK, in September 2016. The 19 revised full papers and 6 keynotes abstracts presented were carefully reviewed and selected from 61 submissions. The papers deal with the application of computational intelligence to open problems in bioinformatics, biostatistics, systems and synthetic biology, medicalinformatics, computational approaches to life sciences in general

Testing Statistical Hypotheses with Given Reliability

Kartlos Joseph Kachiashvili
Testing Statistical Hypotheses with Given Reliability Book PDF

Author : Kartlos Joseph Kachiashvili
Publisher : Cambridge Scholars Publishing
Page : 333 pages
File Size : 50,8 Mb
Release : 2023-06-02
Category : Mathematics
ISBN : 9781527510647

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Testing Statistical Hypotheses with Given Reliability by Kartlos Joseph Kachiashvili Pdf

This book is dedicated to the branch of statistical science which pertains to the theory of hypothesis testing. This involves deciding on the plausibility of two or more hypothetical models based on some data. This work will be both interesting and useful for professional and beginner researchers and practitioners of many fields, who are interested in the theoretical and practical issues of the direction of mathematical statistics, namely, in statistical hypothesis testing. It will also be very useful for specialists of different fields for solving suitable problems at the appropriate level, as the book discusses in detail many important practical problems and provides detailed algorithms for their solutions.

Model-Assisted Bayesian Designs for Dose Finding and Optimization

Ying Yuan,Ruitao Lin,J. Jack Lee
Model Assisted Bayesian Designs for Dose Finding and Optimization Book PDF

Author : Ying Yuan,Ruitao Lin,J. Jack Lee
Publisher : CRC Press
Page : 234 pages
File Size : 52,7 Mb
Release : 2022-11-11
Category : Medical
ISBN : 9780429628474

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Model-Assisted Bayesian Designs for Dose Finding and Optimization by Ying Yuan,Ruitao Lin,J. Jack Lee Pdf

Bayesian adaptive designs provide a critical approach to improve the efficiency and success of drug development that has been embraced by the US Food and Drug Administration (FDA). This is particularly important for early phase trials as they form the basis for the development and success of subsequent phase II and III trials. The objective of this book is to describe the state-of-the-art model-assisted designs to facilitate and accelerate the use of novel adaptive designs for early phase clinical trials. Model-assisted designs possess avant-garde features where superiority meets simplicity. Model-assisted designs enjoy exceptional performance comparable to more complicated model-based adaptive designs, yet their decision rules often can be pre-tabulated and included in the protocol—making implementation as simple as conventional algorithm-based designs. An example is the Bayesian optimal interval (BOIN) design, the first dose-finding design to receive the fit-for-purpose designation from the FDA. This designation underscores the regulatory agency's support of the use of the novel adaptive design to improve drug development. Features Represents the first book to provide comprehensive coverage of model-assisted designs for various types of dose-finding and optimization clinical trials Describes the up-to-date theory and practice for model-assisted designs Presents many practical challenges, issues, and solutions arising from early-phase clinical trials Illustrates with many real trial applications Offers numerous tips and guidance on designing dose finding and optimization trials Provides step-by-step illustrations of using software to design trials Develops a companion website (www.trialdesign.org) to provide freely available, easy-to-use software to assist learning and implementing model-assisted designs Written by internationally recognized research leaders who pioneered model-assisted designs from the University of Texas MD Anderson Cancer Center, this book shows how model-assisted designs can greatly improve the efficiency and simplify the design, conduct, and optimization of early-phase dose-finding trials. It should therefore be a very useful practical reference for biostatisticians, clinicians working in clinical trials, and drug regulatory professionals, as well as graduate students of biostatistics. Novel model-assisted designs showcase the new KISS principle: Keep it simple and smart!

Handbook of Computational Statistics

Yuichi Mori
Handbook of Computational Statistics Book PDF

Author : Yuichi Mori
Publisher : Springer Science & Business Media
Page : 1096 pages
File Size : 51,8 Mb
Release : 2004-07-14
Category : Computers
ISBN : 3540404643

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Handbook of Computational Statistics by Yuichi Mori Pdf

The Handbook of Computational Statistics: Concepts and Methodology is divided into four parts. It begins with an overview over the field of Computational Statistics. The second part presents several topics in the supporting field of statistical computing. Emphasis is placed on the need of fast and accurate numerical algorithms and it discusses some of the basic methodologies for transformation, data base handling and graphics treatment. The third part focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Finally a set of selected applications like Bioinformatics, Medical Imaging, Finance and Network Intrusion Detection highlight the usefulness of computational statistics.

Introductory Statistics with R

Peter Dalgaard
Introductory Statistics with R Book PDF

Author : Peter Dalgaard
Publisher : Springer Science & Business Media
Page : 274 pages
File Size : 50,9 Mb
Release : 2006-04-06
Category : Mathematics
ISBN : 9780387226323

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Introductory Statistics with R by Peter Dalgaard Pdf

This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.

Introductory Biostatistics for the Health Sciences

Michael R. Chernick,Robert H. Friis
Introductory Biostatistics for the Health Sciences Book PDF

Author : Michael R. Chernick,Robert H. Friis
Publisher : John Wiley & Sons
Page : 426 pages
File Size : 46,9 Mb
Release : 2003-06-24
Category : Mathematics
ISBN : 9780471458654

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Introductory Biostatistics for the Health Sciences by Michael R. Chernick,Robert H. Friis Pdf

"Introductory Biostatistics for the Health Sciences" ist eine fundierte Einführung in die Biostatistik und ihre Anwendungsgebiete. Der Band richtet sich vorwiegend an Mediziner und Statistiker. Theorie und Praxis stehen im ausgewogenen Verhältnis, d.h. praktische Anwendungen werden, wo nötig, durch den theoretischen Hintergrund ergänzt. Der Schwerpunkt liegt eindeutig auf der praktischen Anwendung. Der Band geht auch auf jüngste Fortschritte bei der Bootstrap-, Outlier- und Meta-Analyse ein, Themen, die in der Regel in Konkurrenzwerken, nicht behandelt werden. Mit einer Fülle von Übungsaufgaben. Auch Statistiksoftware wird ausführlich besprochen.

Contemporary Biostatistics with Biopharmaceutical Applications

Lanju Zhang,Ding-Geng (Din) Chen,Hongmei Jiang,Gang Li,Hui Quan
Contemporary Biostatistics with Biopharmaceutical Applications Book PDF

Author : Lanju Zhang,Ding-Geng (Din) Chen,Hongmei Jiang,Gang Li,Hui Quan
Publisher : Springer
Page : 336 pages
File Size : 40,6 Mb
Release : 2020-08-14
Category : Medical
ISBN : 3030153126

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Contemporary Biostatistics with Biopharmaceutical Applications by Lanju Zhang,Ding-Geng (Din) Chen,Hongmei Jiang,Gang Li,Hui Quan Pdf

This edited volume presents current research in biostatistics with emphasis on biopharmaceutical applications. Featuring contributions presented at the 2017 ICSA Applied Statistics Symposium held in Chicago, IL on June 25 to 28, 2017, this book explores timely topics that have a high potential impact on statistical methodology and future research in biostatistics and biopharmaceuticals. The theme of this conference was Statistics for a New Generation: Challenges and Opportunities, in recognition of the advent of a new generation of statisticians. The conference attracted statisticians working in academia, government, and industry; domestic and international statisticians. From the conference, the editors selected 28 high-quality presentations and invited the speakers to prepare full chapters for this book. These contributions are divided into four parts: Part I Biostatistical Methodology, Part II Statistical Genetics and Bioinformatics, Part III Regulatory Statistics, and Part IV Biopharmaceutical Research and Applications. Featuring contributions on topics such as statistics in genetics, bioinformatics, biostatistical methodology, and statistical computing, this book is beneficial to researchers, academics, practitioners and policy makers in biostatistics and biopharmaceuticals.

Model Systems in Biology

Georg Striedter
Model Systems in Biology Book PDF

Author : Georg Striedter
Publisher : MIT Press
Page : 303 pages
File Size : 51,8 Mb
Release : 2022-08-23
Category : Science
ISBN : 9780262370035

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Model Systems in Biology by Georg Striedter Pdf

How biomedical research using various animal species and in vitro cellular systems has resulted in both major successes and translational failure. In Model Systems in Biology, comparative neurobiologist Georg Striedter examines how biomedical researchers have used animal species and in vitro cellular systems to understand and develop treatments for human diseases ranging from cancer and polio to Alzheimer’s disease and schizophrenia. Although there have been some major successes, much of this “translational” research on model systems has failed to generalize to humans. Striedter explores the history of such research, focusing on the models used and considering the question of model selection from a variety of perspectives—the philosophical, the historical, and that of practicing biologists. Striedter reviews some philosophical concepts and ethical issues, including concerns over animal suffering and the compromises that result. He traces the history of the most widely used animal and in vitro models, describing how they compete with one another in a changing ecosystem of models. He examines how therapies for bacterial and viral infections, cancer, cardiovascular diseases, and neurological disorders have been developed using animal and cell culture models—and how research into these diseases has both taken advantage of and been hindered by model system differences. Finally, Striedter argues for a “big tent” biology, in which a diverse set of models and research strategies can coexist productively.

Biostatistics

Gerald van Belle,Lloyd D. Fisher,Patrick J. Heagerty,Thomas Lumley
Biostatistics Book PDF

Author : Gerald van Belle,Lloyd D. Fisher,Patrick J. Heagerty,Thomas Lumley
Publisher : John Wiley & Sons
Page : 894 pages
File Size : 48,5 Mb
Release : 2004-10-06
Category : Medical
ISBN : 9780471602354

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Biostatistics by Gerald van Belle,Lloyd D. Fisher,Patrick J. Heagerty,Thomas Lumley Pdf

A respected introduction to biostatistics, thoroughly updated and revised The first edition of Biostatistics: A Methodology for the Health Sciences has served professionals and students alike as a leading resource for learning how to apply statistical methods to the biomedical sciences. This substantially revised Second Edition brings the book into the twenty-first century for today’s aspiring and practicing medical scientist. This versatile reference provides a wide-ranging look at basic and advanced biostatistical concepts and methods in a format calibrated to individual interests and levels of proficiency. Written with an eye toward the use of computer applications, the book examines the design of medical studies, descriptive statistics, and introductory ideas of probability theory and statistical inference; explores more advanced statistical methods; and illustrates important current uses of biostatistics. New to this edition are discussions of Longitudinal data analysis Randomized clinical trials Bayesian statistics GEE The bootstrap method Enhanced by a companion Web site providing data sets, selected problems and solutions, and examples from such current topics as HIV/AIDS, this is a thoroughly current, comprehensive introduction to the field.

Statistical Causal Inferences and Their Applications in Public Health Research

Hua He,Pan Wu,Ding-Geng (Din) Chen
Statistical Causal Inferences and Their Applications in Public Health Research Book PDF

Author : Hua He,Pan Wu,Ding-Geng (Din) Chen
Publisher : Springer
Page : 321 pages
File Size : 51,8 Mb
Release : 2018-06-23
Category : Medical
ISBN : 3319823086

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Statistical Causal Inferences and Their Applications in Public Health Research by Hua He,Pan Wu,Ding-Geng (Din) Chen Pdf

This book compiles and presents new developments in statistical causal inference. The accompanying data and computer programs are publicly available so readers may replicate the model development and data analysis presented in each chapter. In this way, methodology is taught so that readers may implement it directly. The book brings together experts engaged in causal inference research to present and discuss recent issues in causal inference methodological development. This is also a timely look at causal inference applied to scenarios that range from clinical trials to mediation and public health research more broadly. In an academic setting, this book will serve as a reference and guide to a course in causal inference at the graduate level (Master's or Doctorate). It is particularly relevant for students pursuing degrees in statistics, biostatistics, and computational biology. Researchers and data analysts in public health and biomedical research will also find this book to be an important reference.