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Bayesian Dose Response Modeling In Sparse Data
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Book Synopsis Applied Bayesian Hierarchical Methods by : Peter D. Congdon
Download or read book Applied Bayesian Hierarchical Methods written by Peter D. Congdon and published by CRC Press. This book was released on 2010-05-19 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of Markov chain Monte Carlo (MCMC) methods for estimating hierarchical models involves complex data structures and is often described as a revolutionary development. An intermediate-level treatment of Bayesian hierarchical models and their applications, Applied Bayesian Hierarchical Methods demonstrates the advantages of a Bayesian approach
Book Synopsis Bayesian Data Analysis, Third Edition by : Andrew Gelman
Download or read book Bayesian Data Analysis, Third Edition written by Andrew Gelman and published by CRC Press. This book was released on 2013-11-01 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Book Synopsis Uncertainty Modeling in Dose Response by : Roger M. Cooke
Download or read book Uncertainty Modeling in Dose Response written by Roger M. Cooke and published by John Wiley & Sons. This book was released on 2009-05-20 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: A valuable guide to understanding the problem of quantifying uncertainty in dose response relations for toxic substances In today's scientific research, there exists the need to address the topic of uncertainty as it pertains to dose response modeling. Uncertainty Modeling in Dose Response is the first book of its kind to implement and compare different methods for quantifying the uncertainty in the probability of response, as a function of dose. This volume gathers leading researchers in the field to properly address the issue while communicating concepts from diverse viewpoints and incorporating valuable insights. The result is a collection that reveals the properties, strengths, and weaknesses that exist in the various approaches to bench test problems. This book works with four bench test problems that were taken from real bioassay data for hazardous substances currently under study by the United States Environmental Protection Agency (EPA). The use of actual data provides readers with information that is relevant and representative of the current work being done in the field. Leading contributors from the toxicology and risk assessment communities have applied their methods to quantify model uncertainty in dose response for each case by employing various approaches, including Benchmark Dose Software methods, probabilistic inversion with isotonic regression, nonparametric Bayesian modeling, and Bayesian model averaging. Each chapter is reviewed and critiqued from three professional points of view: risk analyst/regulator, statistician/mathematician, and toxicologist/epidemiologist. In addition, all methodologies are worked out in detail, allowing readers to replicate these analyses and gain a thorough understanding of the methods. Uncertainty Modeling in Dose Response is an excellent book for courses on risk analysis and biostatistics at the upper-undergraduate and graduate levels. It also serves as a valuable reference for risk assessment, toxicology, biostatistics, and environmental chemistry professionals who wish to expand their knowledge and expertise in statistical dose response modeling problems and approaches.
Book Synopsis Bayesian Inference by : Javier Prieto Tejedor
Download or read book Bayesian Inference written by Javier Prieto Tejedor and published by BoD – Books on Demand. This book was released on 2017-11-02 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: The range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been extensively applied to logistics, medical services, search and rescue operations, or automotive safety, among others. This book takes a look at both theoretical foundations of Bayesian inference and practical implementations in different fields. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics, as well as a source document of fundamentals for intermediate Bayesian readers.
Book Synopsis Bayesian Methods in Pharmaceutical Research by : Emmanuel Lesaffre
Download or read book Bayesian Methods in Pharmaceutical Research written by Emmanuel Lesaffre and published by CRC Press. This book was released on 2020-04-15 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care interventions. In 2010, the first Applied Bayesian Biostatistics conference was held, with the primary objective to stimulate the practical implementation of Bayesian statistics, and to promote the added-value for accelerating the discovery and the delivery of new cures to patients. This book is a synthesis of the conferences and debates, providing an overview of Bayesian methods applied to nearly all stages of research and development, from early discovery to portfolio management. It highlights the value associated with sharing a vision with the regulatory authorities, academia, and pharmaceutical industry, with a view to setting up a common strategy for the appropriate use of Bayesian statistics for the benefit of patients. The book covers: Theory, methods, applications, and computing Bayesian biostatistics for clinical innovative designs Adding value with Real World Evidence Opportunities for rare, orphan diseases, and pediatric development Applied Bayesian biostatistics in manufacturing Decision making and Portfolio management Regulatory perspective and public health policies Statisticians and data scientists involved in the research, development, and approval of new cures will be inspired by the possible applications of Bayesian methods covered in the book. The methods, applications, and computational guidance will enable the reader to apply Bayesian methods in their own pharmaceutical research.
Book Synopsis Bayesian Inference and Computation in Reliability and Survival Analysis by : Yuhlong Lio
Download or read book Bayesian Inference and Computation in Reliability and Survival Analysis written by Yuhlong Lio and published by Springer Nature. This book was released on 2022-08-01 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian analysis is one of the important tools for statistical modelling and inference. Bayesian frameworks and methods have been successfully applied to solve practical problems in reliability and survival analysis, which have a wide range of real world applications in medical and biological sciences, social and economic sciences, and engineering. In the past few decades, significant developments of Bayesian inference have been made by many researchers, and advancements in computational technology and computer performance has laid the groundwork for new opportunities in Bayesian computation for practitioners. Because these theoretical and technological developments introduce new questions and challenges, and increase the complexity of the Bayesian framework, this book brings together experts engaged in groundbreaking research on Bayesian inference and computation to discuss important issues, with emphasis on applications to reliability and survival analysis. Topics covered are timely and have the potential to influence the interacting worlds of biostatistics, engineering, medical sciences, statistics, and more. The included chapters present current methods, theories, and applications in the diverse area of biostatistical analysis. The volume as a whole serves as reference in driving quality global health research.
Book Synopsis Encyclopedia of Biopharmaceutical Statistics - Four Volume Set by : Shein-Chung Chow
Download or read book Encyclopedia of Biopharmaceutical Statistics - Four Volume Set written by Shein-Chung Chow and published by CRC Press. This book was released on 2018-09-03 with total page 4031 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the first edition in 2000, there has been an explosive growth of literature in biopharmaceutical research and development of new medicines. This encyclopedia (1) provides a comprehensive and unified presentation of designs and analyses used at different stages of the drug development process, (2) gives a well-balanced summary of current regulatory requirements, and (3) describes recently developed statistical methods in the pharmaceutical sciences. Features of the Fourth Edition: 1. 78 new and revised entries have been added for a total of 308 chapters and a fourth volume has been added to encompass the increased number of chapters. 2. Revised and updated entries reflect changes and recent developments in regulatory requirements for the drug review/approval process and statistical designs and methodologies. 3. Additional topics include multiple-stage adaptive trial design in clinical research, translational medicine, design and analysis of biosimilar drug development, big data analytics, and real world evidence for clinical research and development. 4. A table of contents organized by stages of biopharmaceutical development provides easy access to relevant topics. About the Editor: Shein-Chung Chow, Ph.D. is currently an Associate Director, Office of Biostatistics, U.S. Food and Drug Administration (FDA). Dr. Chow is an Adjunct Professor at Duke University School of Medicine, as well as Adjunct Professor at Duke-NUS, Singapore and North Carolina State University. Dr. Chow is the Editor-in-Chief of the Journal of Biopharmaceutical Statistics and the Chapman & Hall/CRC Biostatistics Book Series and the author of 28 books and over 300 methodology papers. He was elected Fellow of the American Statistical Association in 1995.
Book Synopsis Case Studies in Bayesian Statistics by : Constantine Gatsonis
Download or read book Case Studies in Bayesian Statistics written by Constantine Gatsonis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past few years have witnessed dramatic advances in computational methods for Bayesian inference. As a result, Bayesian approaches to solving a wide variety of problems in data analysis and decision-making have become feasible, and there is currently a growth spurt in the application of Bayesian methods. The purpose of this volume is to present several detailed examples of applications of Bayesian thinking, with an emphasis on the scientific or technological context of the problem being solved. The papers collected here were presented and discussed at a Workshop held at Carnegie-Mellon University, September 29 through October 1, 1991. There are five ma jor articles, each with two discussion pieces and a reply. These articles were invited by us following a public solicitation of abstracts. The problems they address are diverse, but all bear on policy decision-making. Though not part of our original design for the Workshop, that commonality of theme does emphasize the usefulness of Bayesian meth ods in this arena. Along with the invited papers were several additional commentaries of a general nature; the first comment was invited and the remainder grew out of the discussion at the Workshop. In addition there are nine contributed papers, selected from the thirty-four presented at the Workshop, on a variety of applications. This collection of case studies illustrates the ways in which Bayesian methods are being incorporated into statistical practice. The strengths (and limitations) of the approach become apparent through the examples.
Book Synopsis Quantitative Decisions in Drug Development by : Christy Chuang-Stein
Download or read book Quantitative Decisions in Drug Development written by Christy Chuang-Stein and published by Springer. This book was released on 2017-05-25 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a high-level treatise of evidence-based decisions in drug development. Because of the inseparable relationship between designs and decisions, a good portion of this book is devoted to the design of clinical trials. The book begins with an overview of product development and regulatory approval pathways. It then discusses how to incorporate prior knowledge into study design and decision making at different stages of drug development. The latter include selecting appropriate metrics to formulate decisions criteria, determining go/no-go decisions for progressing a drug candidate to the next stage and predicting the effectiveness of a product. Lastly, it points out common mistakes made by drug developers under the current drug-development paradigm. The book offers useful insights to statisticians, clinicians, regulatory affairs managers and decision-makers in the pharmaceutical industry who have a basic understanding of the drug-development process and the clinical trials conducted to support drug-marketing authorization. The authors provide software codes for select analytical approaches discussed in the book. The book includes enough technical details to allow statisticians to replicate the quantitative illustrations so that they can generate information to facilitate decision-making themselves.
Book Synopsis Bayesian Designs for Phase I-II Clinical Trials by : Ying Yuan
Download or read book Bayesian Designs for Phase I-II Clinical Trials written by Ying Yuan and published by CRC Press. This book was released on 2017-12-19 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reliably optimizing a new treatment in humans is a critical first step in clinical evaluation since choosing a suboptimal dose or schedule may lead to failure in later trials. At the same time, if promising preclinical results do not translate into a real treatment advance, it is important to determine this quickly and terminate the clinical evaluation process to avoid wasting resources. Bayesian Designs for Phase I–II Clinical Trials describes how phase I–II designs can serve as a bridge or protective barrier between preclinical studies and large confirmatory clinical trials. It illustrates many of the severe drawbacks with conventional methods used for early-phase clinical trials and presents numerous Bayesian designs for human clinical trials of new experimental treatment regimes. Written by research leaders from the University of Texas MD Anderson Cancer Center, this book shows how Bayesian designs for early-phase clinical trials can explore, refine, and optimize new experimental treatments. It emphasizes the importance of basing decisions on both efficacy and toxicity.
Book Synopsis Regulatory Toxicology by : Franz-Xaver Reichl
Download or read book Regulatory Toxicology written by Franz-Xaver Reichl and published by Springer. This book was released on 2014-03-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will be written by experts for professionals, scientists and all those involved in toxicological data generation and decision-making. It is the updated and expanded version of a monograph published in German in 2004. Chemical safety is regulated on various levels including production, storage, transport, handling, disposal or labelling. This book deals comprehensively with the safety-ensuring methods and concepts employed by regulatory agencies, industry and academics. Toxicologists use experimental and scientific approaches for data collection, e.g. about chemical hazards, physicochemical features or toxicokinetics. The respective experimental methods are described in the book. Toxicologists also deal with much insecurity in the exposure and effect scenarios during risk assessment. To overcome these, they have different extrapolation methods and estimation procedures at their disposal. The book describes these methods in an accessible manner. Differing concepts from one regulation area to another are also covered. Reasons and consequences become evident when reading the book. Altogether, the book Regulatory Toxicology will serve as an excellent reference.
Book Synopsis Handbook of Meta-Analysis by : Christopher H. Schmid
Download or read book Handbook of Meta-Analysis written by Christopher H. Schmid and published by CRC Press. This book was released on 2020-09-07 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1. Provides a comprehensive overview of meta-analysis methods and applications. 2. Divided into four major sub-topics, covering univariate meta-analysis, multivariate, applications and policy. 3. Designed to be suitable for graduate students and researchers new to the field. 4. Includes lots of real examples, with data and software code made available. 5. Chapters written by the leading researchers in the field.
Book Synopsis mODa 10 – Advances in Model-Oriented Design and Analysis by : Dariusz Ucinski
Download or read book mODa 10 – Advances in Model-Oriented Design and Analysis written by Dariusz Ucinski and published by Springer Science & Business Media. This book was released on 2013-03-21 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects the proceedings of the 10th Workshop on Model-Oriented Design and Analysis (mODa). A model-oriented view on the design of experiments, which is the unifying theme of all mODa meetings, assumes some knowledge of the form of the data-generating process and naturally leads to the so-called optimum experimental design. Its theory and practice have since become important in many scientific and technological fields, ranging from optimal designs for dynamic models in pharmacological research, to designs for industrial experimentation, to designs for simulation experiments in environmental risk management, to name but a few. The methodology has become even more important in recent years because of the increased speed of scientific developments, the complexity of the systems currently under investigation and the mounting pressure on businesses, industries and scientific researchers to reduce product and process development times. This increased competition requires ever increasing efficiency in experimentation, thus necessitating new statistical designs. This book presents a rich collection of carefully selected contributions ranging from statistical methodology to emerging applications. It primarily aims to provide an overview of recent advances and challenges in the field, especially in the context of new formulations, methods and state-of-the-art algorithms. The topics included in this volume will be of interest to all scientists and engineers and statisticians who conduct experiments.
Book Synopsis Simulation for Designing Clinical Trials by : Hui Kimko
Download or read book Simulation for Designing Clinical Trials written by Hui Kimko and published by CRC Press. This book was released on 2002-12-12 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing more than just a comprehensive history, critical vocabulary, insightful compilation of motivations, and clear explanation of the state-of-the-art of modern clinical trial simulation, this book supplies a rigorous framework for employing simulation as an experiment, according to a predefined simulation plan, that reflects good simulation p
Book Synopsis Applied Pharmacometrics by : Stephan Schmidt
Download or read book Applied Pharmacometrics written by Stephan Schmidt and published by Springer. This book was released on 2014-12-01 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive volume provides an update on the current state of pharmacometrics in drug development. It consists of nineteen chapters all written by leading scientists from the pharmaceutical industry, regulatory agencies and academia. After an introduction of the basic pharmacokinetic and pharmacodynamic concepts of pharmacometrics in drug development, the book presents numerous examples of specific applications that utilize pharmacometrics with modeling and simulations over a variety of therapeutic areas, including pediatrics, diabetes, obesity, infections, psychiatrics, Alzheimer’s disease, and dermatology, among others. The examples illustrate how results from all phases of drug development can be integrated in a more timely and cost-effective process. Applying pharmacometric decision tools during drug development can allow objective, data-based decision making. At the same time, the process can identify redundant or unnecessary experiments as well as some costly clinical trials that can be avoided. In addition to cost saving by expedited development of successful drug candidates, pharmacometrics has an important economic impact in drug product selection. Unsuccessful drug candidates can be identified early and discontinued without expending efforts required for additional studies and allocating limited resources. Hence, pharmacometric modeling and simulation has become a powerful tool to bring new and better medications to the patient at a faster pace and with greater probability of success.
Book Synopsis Bioequivalence and Statistics in Clinical Pharmacology by : Scott D. Patterson
Download or read book Bioequivalence and Statistics in Clinical Pharmacology written by Scott D. Patterson and published by CRC Press. This book was released on 2017-03-27 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Maintaining a practical perspective, Bioequivalence and Statistics in Clinical Pharmacology, Second Edition explores statistics used in day-to-day clinical pharmacology work. The book is a starting point for those involved in such research and covers the methods needed to design, analyze, and interpret bioequivalence trials; explores when, how, and why these studies are performed as part of drug development; and demonstrates the methods using real world examples. Drawing on knowledge gained directly from working in the pharmaceutical industry, the authors set the stage by describing the general role of statistics. Once the foundation of clinical pharmacology drug development, regulatory applications, and the design and analysis of bioequivalence trials are established, including recent regulatory changes in design and analysis and in particular sample-size adaptation, they move on to related topics in clinical pharmacology involving the use of cross-over designs. These include, but are not limited to, safety studies in Phase I, dose-response trials, drug interaction trials, food-effect and combination trials, QTc and other pharmacodynamic equivalence trials, proof-of-concept trials, dose-proportionality trials, and vaccines trials. This second edition addresses several recent developments in the field, including new chapters on adaptive bioequivalence studies, scaled average bioequivalence testing, and vaccine trials. Purposefully designed to be instantly applicable, Bioequivalence and Statistics in Clinical Pharmacology, Second Edition provides examples of SAS and R code so that the analyses described can be immediately implemented. The authors have made extensive use of the proc mixed procedures available in SAS.
Book Synopsis Bayesian inference with INLA by : Virgilio Gomez-Rubio
Download or read book Bayesian inference with INLA written by Virgilio Gomez-Rubio and published by CRC Press. This book was released on 2020-02-20 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: The integrated nested Laplace approximation (INLA) is a recent computational method that can fit Bayesian models in a fraction of the time required by typical Markov chain Monte Carlo (MCMC) methods. INLA focuses on marginal inference on the model parameters of latent Gaussian Markov random fields models and exploits conditional independence properties in the model for computational speed. Bayesian Inference with INLA provides a description of INLA and its associated R package for model fitting. This book describes the underlying methodology as well as how to fit a wide range of models with R. Topics covered include generalized linear mixed-effects models, multilevel models, spatial and spatio-temporal models, smoothing methods, survival analysis, imputation of missing values, and mixture models. Advanced features of the INLA package and how to extend the number of priors and latent models available in the package are discussed. All examples in the book are fully reproducible and datasets and R code are available from the book website. This book will be helpful to researchers from different areas with some background in Bayesian inference that want to apply the INLA method in their work. The examples cover topics on biostatistics, econometrics, education, environmental science, epidemiology, public health, and the social sciences.
