Statistical Methods For Dynamic Treatment Regimes

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Dynamic Treatment Regimes

Anastasios A. Tsiatis
Dynamic Treatment Regimes Book PDF

Author : Anastasios A. Tsiatis
Publisher : CRC Press
Page : 602 pages
File Size : 49,7 Mb
Release : 2019-12-19
Category : Mathematics
ISBN : 9781498769785

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Dynamic Treatment Regimes by Anastasios A. Tsiatis Pdf

Dynamic Treatment Regimes: Statistical Methods for Precision Medicine provides a comprehensive introduction to statistical methodology for the evaluation and discovery of dynamic treatment regimes from data. Researchers and graduate students in statistics, data science, and related quantitative disciplines with a background in probability and statistical inference and popular statistical modeling techniques will be prepared for further study of this rapidly evolving field. A dynamic treatment regime is a set of sequential decision rules, each corresponding to a key decision point in a disease or disorder process, where each rule takes as input patient information and returns the treatment option he or she should receive. Thus, a treatment regime formalizes how a clinician synthesizes patient information and selects treatments in practice. Treatment regimes are of obvious relevance to precision medicine, which involves tailoring treatment selection to patient characteristics in an evidence-based way. Of critical importance to precision medicine is estimation of an optimal treatment regime, one that, if used to select treatments for the patient population, would lead to the most beneficial outcome on average. Key methods for estimation of an optimal treatment regime from data are motivated and described in detail. A dedicated companion website presents full accounts of application of the methods using a comprehensive R package developed by the authors. The authors’ website www.dtr-book.com includes updates, corrections, new papers, and links to useful websites.

Statistical Methods for Dynamic Treatment Regimes

Bibhas Chakraborty,Erica E.M. Moodie
Statistical Methods for Dynamic Treatment Regimes Book PDF

Author : Bibhas Chakraborty,Erica E.M. Moodie
Publisher : Springer Science & Business Media
Page : 204 pages
File Size : 45,5 Mb
Release : 2013-07-23
Category : Medical
ISBN : 9781461474289

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Statistical Methods for Dynamic Treatment Regimes by Bibhas Chakraborty,Erica E.M. Moodie Pdf

Statistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine. This volume demonstrates these methods with their conceptual underpinnings and illustration through analysis of real and simulated data. These methods are immediately applicable to the practice of personalized medicine, which is a medical paradigm that emphasizes the systematic use of individual patient information to optimize patient health care. This is the first single source to provide an overview of methodology and results gathered from journals, proceedings, and technical reports with the goal of orienting researchers to the field. The first chapter establishes context for the statistical reader in the landscape of personalized medicine. Readers need only have familiarity with elementary calculus, linear algebra, and basic large-sample theory to use this text. Throughout the text, authors direct readers to available code or packages in different statistical languages to facilitate implementation. In cases where code does not already exist, the authors provide analytic approaches in sufficient detail that any researcher with knowledge of statistical programming could implement the methods from scratch. This will be an important volume for a wide range of researchers, including statisticians, epidemiologists, medical researchers, and machine learning researchers interested in medical applications. Advanced graduate students in statistics and biostatistics will also find material in Statistical Methods for Dynamic Treatment Regimes to be a critical part of their studies.

Dynamic Treatment Regimes

Anastasios A. Tsiatis,Shannon T. Holloway
Dynamic Treatment Regimes Book PDF

Author : Anastasios A. Tsiatis,Shannon T. Holloway
Publisher : CRC Press
Page : 602 pages
File Size : 51,5 Mb
Release : 2019-12-10
Category : Medical records
ISBN : 1498769772

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Dynamic Treatment Regimes by Anastasios A. Tsiatis,Shannon T. Holloway Pdf

"Precision medicine seeks to use data to construct principled, i.e., evidence-based, treatment strategies that dictate where, when, and to whom treatment should be applied. This book provides an accessible yet comprehensive introduction to statistical methodology for dynamic treatment regimes"--

Adaptive Treatment Strategies in Practice: Planning Trials and Analyzing Data for Personalized Medicine

Michael R. Kosorok,Erica E. M. Moodie
Adaptive Treatment Strategies in Practice Planning Trials and Analyzing Data for Personalized Medicine Book PDF

Author : Michael R. Kosorok,Erica E. M. Moodie
Publisher : SIAM
Page : 348 pages
File Size : 44,5 Mb
Release : 2015-12-08
Category : Medical
ISBN : 9781611974188

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Adaptive Treatment Strategies in Practice: Planning Trials and Analyzing Data for Personalized Medicine by Michael R. Kosorok,Erica E. M. Moodie Pdf

Personalized medicine is a medical paradigm that emphasizes systematic use of individual patient information to optimize that patient's health care, particularly in managing chronic conditions and treating cancer. In the statistical literature, sequential decision making is known as an adaptive treatment strategy (ATS) or a dynamic treatment regime (DTR). The field of DTRs emerges at the interface of statistics, machine learning, and biomedical science to provide a data-driven framework for precision medicine. The authors provide a learning-by-seeing approach to the development of ATSs, aimed at a broad audience of health researchers. All estimation procedures used are described in sufficient heuristic and technical detail so that less quantitative readers can understand the broad principles underlying the approaches. At the same time, more quantitative readers can implement these practices. This book provides the most up-to-date summary of the current state of the statistical research in personalized medicine; contains chapters by leaders in the area from both the statistics and computer sciences fields; and also contains a range of practical advice, introductory and expository materials, and case studies.

Statistical Remedies for Medical Researchers

Peter F. Thall
Statistical Remedies for Medical Researchers Book PDF

Author : Peter F. Thall
Publisher : Springer Nature
Page : 297 pages
File Size : 55,9 Mb
Release : 2020-03-12
Category : Medical
ISBN : 9783030437145

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Statistical Remedies for Medical Researchers by Peter F. Thall Pdf

This book illustrates numerous statistical practices that are commonly used by medical researchers, but which have severe flaws that may not be obvious. For each example, it provides one or more alternative statistical methods that avoid misleading or incorrect inferences being made. The technical level is kept to a minimum to make the book accessible to non-statisticians. At the same time, since many of the examples describe methods used routinely by medical statisticians with formal statistical training, the book appeals to a broad readership in the medical research community.

Proceedings of the Second Seattle Symposium in Biostatistics

Danyu Lin,Patrick J. Heagerty
Proceedings of the Second Seattle Symposium in Biostatistics Book PDF

Author : Danyu Lin,Patrick J. Heagerty
Publisher : Springer Science & Business Media
Page : 332 pages
File Size : 47,9 Mb
Release : 2012-12-06
Category : Medical
ISBN : 9781441990761

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Proceedings of the Second Seattle Symposium in Biostatistics by Danyu Lin,Patrick J. Heagerty Pdf

This volume contains a selection of papers presented at the Second Seattle Symposium in Biostatistics: Analysis of Correlated Data. The symposium was held in 2000 to celebrate the 30th anniversary of the University of Washington School of Public Health and Community Medicine. It featured keynote lectures by Norman Breslow, David Cox and Ross Prentice and 16 invited presentations by other prominent researchers. The papers contained in this volume encompass recent methodological advances in several important areas, such as longitudinal data, multivariate failure time data and genetic data, as well as innovative applications of the existing theory and methods. This volume is a valuable reference for researchers and practitioners in the field of correlated data analysis.

Exposure-Response Modeling

Jixian Wang
Exposure Response Modeling Book PDF

Author : Jixian Wang
Publisher : CRC Press
Page : 348 pages
File Size : 44,7 Mb
Release : 2015-07-17
Category : Mathematics
ISBN : 9781466573215

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Exposure-Response Modeling by Jixian Wang Pdf

Discover the Latest Statistical Approaches for Modeling Exposure-Response RelationshipsWritten by an applied statistician with extensive practical experience in drug development, Exposure-Response Modeling: Methods and Practical Implementation explores a wide range of topics in exposure-response modeling, from traditional pharmacokinetic-pharmacody

Design and Analysis of Subgroups with Biopharmaceutical Applications

Naitee Ting,Joseph C. Cappelleri,Shuyen Ho,(Din) Ding-Geng Chen
Design and Analysis of Subgroups with Biopharmaceutical Applications Book PDF

Author : Naitee Ting,Joseph C. Cappelleri,Shuyen Ho,(Din) Ding-Geng Chen
Publisher : Springer Nature
Page : 404 pages
File Size : 48,5 Mb
Release : 2020-05-01
Category : Medical
ISBN : 9783030401054

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Design and Analysis of Subgroups with Biopharmaceutical Applications by Naitee Ting,Joseph C. Cappelleri,Shuyen Ho,(Din) Ding-Geng Chen Pdf

This book provides an overview of the theories and applications on subgroups in the biopharmaceutical industry. Drawing from a range of expert perspectives in academia and industry, this collection offers an overarching dialogue about recent advances in biopharmaceutical applications, novel statistical and methodological developments, and potential future directions. The volume covers topics in subgroups in clinical trial design; subgroup identification and personalized medicine; and general issues in subgroup analyses, including regulatory ones. Included chapters present current methods, theories, and case applications in the diverse field of subgroup application and analysis. Offering timely perspectives from a range of authoritative sources, the volume is designed to have wide appeal to professionals in the pharmaceutical industry and to graduate students and researchers in academe and government.

Targeted Learning

Mark J. van der Laan,Sherri Rose
Targeted Learning Book PDF

Author : Mark J. van der Laan,Sherri Rose
Publisher : Springer Science & Business Media
Page : 628 pages
File Size : 45,6 Mb
Release : 2011-06-17
Category : Mathematics
ISBN : 9781441997821

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Targeted Learning by Mark J. van der Laan,Sherri Rose Pdf

The statistics profession is at a unique point in history. The need for valid statistical tools is greater than ever; data sets are massive, often measuring hundreds of thousands of measurements for a single subject. The field is ready to move towards clear objective benchmarks under which tools can be evaluated. Targeted learning allows (1) the full generalization and utilization of cross-validation as an estimator selection tool so that the subjective choices made by humans are now made by the machine, and (2) targeting the fitting of the probability distribution of the data toward the target parameter representing the scientific question of interest. This book is aimed at both statisticians and applied researchers interested in causal inference and general effect estimation for observational and experimental data. Part I is an accessible introduction to super learning and the targeted maximum likelihood estimator, including related concepts necessary to understand and apply these methods. Parts II-IX handle complex data structures and topics applied researchers will immediately recognize from their own research, including time-to-event outcomes, direct and indirect effects, positivity violations, case-control studies, censored data, longitudinal data, and genomic studies.

Flexible Imputation of Missing Data, Second Edition

Stef van Buuren
Flexible Imputation of Missing Data Second Edition Book PDF

Author : Stef van Buuren
Publisher : CRC Press
Page : 444 pages
File Size : 51,7 Mb
Release : 2018-07-17
Category : Mathematics
ISBN : 9780429960352

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Flexible Imputation of Missing Data, Second Edition by Stef van Buuren Pdf

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between these replacements reflects our ignorance of the true (but missing) value. Each of the completed data set is then analyzed by standard methods, and the results are pooled to obtain unbiased estimates with correct confidence intervals. Multiple imputation is a general approach that also inspires novel solutions to old problems by reformulating the task at hand as a missing-data problem. This is the second edition of a popular book on multiple imputation, focused on explaining the application of methods through detailed worked examples using the MICE package as developed by the author. This new edition incorporates the recent developments in this fast-moving field. This class-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by verbal statements that explain the formula in accessible terms. The book sharpens the reader’s intuition on how to think about missing data, and provides all the tools needed to execute a well-grounded quantitative analysis in the presence of missing data.

Probabilistic Networks and Expert Systems

Robert G. Cowell,Philip Dawid,Steffen L. Lauritzen,David J. Spiegelhalter
Probabilistic Networks and Expert Systems Book PDF

Author : Robert G. Cowell,Philip Dawid,Steffen L. Lauritzen,David J. Spiegelhalter
Publisher : Springer Science & Business Media
Page : 340 pages
File Size : 46,6 Mb
Release : 2007-07-16
Category : Computers
ISBN : 0387718230

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Probabilistic Networks and Expert Systems by Robert G. Cowell,Philip Dawid,Steffen L. Lauritzen,David J. Spiegelhalter Pdf

Probabilistic expert systems are graphical networks which support the modeling of uncertainty and decisions in large complex domains, while retaining ease of calculation. Building on original research by the authors, this book gives a thorough and rigorous mathematical treatment of the underlying ideas, structures, and algorithms. The book will be of interest to researchers in both artificial intelligence and statistics, who desire an introduction to this fascinating and rapidly developing field. The book, winner of the DeGroot Prize 2002, the only book prize in the field of statistics, is new in paperback.

Bayesian Designs for Phase I-II Clinical Trials

Ying Yuan,Hoang Q. Nguyen,Peter F. Thall
Bayesian Designs for Phase I II Clinical Trials Book PDF

Author : Ying Yuan,Hoang Q. Nguyen,Peter F. Thall
Publisher : CRC Press
Page : 233 pages
File Size : 51,6 Mb
Release : 2017-12-19
Category : Mathematics
ISBN : 9781315354224

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Bayesian Designs for Phase I-II Clinical Trials by Ying Yuan,Hoang Q. Nguyen,Peter F. Thall Pdf

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.

Cancer Clinical Trials

Stephen L. George,Xiaofei Wang,Herbert Pang
Cancer Clinical Trials Book PDF

Author : Stephen L. George,Xiaofei Wang,Herbert Pang
Publisher : CRC Press
Page : 474 pages
File Size : 52,6 Mb
Release : 2016-08-19
Category : Mathematics
ISBN : 9781498706902

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Cancer Clinical Trials by Stephen L. George,Xiaofei Wang,Herbert Pang Pdf

Cancer Clinical Trials: Current and Controversial Issues in Design and Analysis provides statisticians with an understanding of the critical challenges currently encountered in oncology trials. Well-known statisticians from academic institutions, regulatory and government agencies (such as the U.S. FDA and National Cancer Institute), and the pharmaceutical industry share their extensive experiences in cancer clinical trials and present examples taken from actual trials. The book covers topics that are often perplexing and sometimes controversial in cancer clinical trials. Most of the issues addressed are also important for clinical trials in other settings. After discussing general topics, the book focuses on aspects of early and late phase clinical trials. It also explores personalized medicine, including biomarker-based clinical trials, adaptive clinical trial designs, and dynamic treatment regimes.

Applied Statistical Methods in Agriculture, Health and Life Sciences

Bayo Lawal
Applied Statistical Methods in Agriculture Health and Life Sciences Book PDF

Author : Bayo Lawal
Publisher : Springer
Page : 799 pages
File Size : 51,8 Mb
Release : 2014-09-15
Category : Medical
ISBN : 9783319055558

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Applied Statistical Methods in Agriculture, Health and Life Sciences by Bayo Lawal Pdf

This textbook teaches crucial statistical methods to answer research questions using a unique range of statistical software programs, including MINITAB and R. This textbook is developed for undergraduate students in agriculture, nursing, biology and biomedical research. Graduate students will also find it to be a useful way to refresh their statistics skills and to reference software options. The unique combination of examples is approached using MINITAB and R for their individual strengths. Subjects covered include among others data description, probability distributions, experimental design, regression analysis, randomized design and biological assay. Unlike other biostatistics textbooks, this text also includes outliers, influential observations in regression and an introduction to survival analysis. Material is taken from the author's extensive teaching and research in Africa, USA and the UK. Sample problems, references and electronic supplementary material accompany each chapter.

Targeted Learning in Data Science

Mark J. van der Laan,Sherri Rose
Targeted Learning in Data Science Book PDF

Author : Mark J. van der Laan,Sherri Rose
Publisher : Springer
Page : 640 pages
File Size : 46,8 Mb
Release : 2018-03-28
Category : Mathematics
ISBN : 9783319653044

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Targeted Learning in Data Science by Mark J. van der Laan,Sherri Rose Pdf

This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap to translate real-world data science applications into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators. These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data with time-dependent confounding, as well as other estimands in dependent data structures, such as networks. Included in Targeted Learning in Data Science are demonstrations with soft ware packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists. Th is book is a sequel to the first textbook on machine learning for causal inference, Targeted Learning, published in 2011. Mark van der Laan, PhD, is Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at UC Berkeley. His research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal inference, and targeted learning. Dr. van der Laan received the 2004 Mortimer Spiegelman Award, the 2005 Van Dantzig Award, the 2005 COPSS Snedecor Award, the 2005 COPSS Presidential Award, and has graduated over 40 PhD students in biostatistics and statistics. Sherri Rose, PhD, is Associate Professor of Health Care Policy (Biostatistics) at Harvard Medical School. Her work is centered on developing and integrating innovative statistical approaches to advance human health. Dr. Rose’s methodological research focuses on nonparametric machine learning for causal inference and prediction. She co-leads the Health Policy Data Science Lab and currently serves as an associate editor for the Journal of the American Statistical Association and Biostatistics.